R-universe search: differential polyadenylationsite usage

r-lib

lintr:A 'Linter' for R Code

Checks adherence to a given style, syntax errors and possible semantic issues. Supports on the fly checking of R code edited with 'RStudio IDE', 'Emacs', 'Vim', 'Sublime Text', 'Atom' and 'Visual Studio Code'.

Maintained by Michael Chirico. Last updated 8 days ago.

linter

83.1 match 1.2k stars 17.00 score 916 scripts 33 dependents

bioc

compcodeR:RNAseq data simulation, differential expression analysis and performance comparison of differential expression methods

This package provides extensive functionality for comparing results obtained by different methods for differential expression analysis of RNAseq data. It also contains functions for simulating count data. Finally, it provides convenient interfaces to several packages for performing the differential expression analysis. These can also be used as templates for setting up and running a user-defined differential analysis workflow within the framework of the package.

Maintained by Charlotte Soneson. Last updated 3 months ago.

immunooncology rnaseq differentialexpression

58.5 match 11 stars 8.06 score 26 scripts

r-forge

deSolve:Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE')

Functions that solve initial value problems of a system of first-order ordinary differential equations ('ODE'), of partial differential equations ('PDE'), of differential algebraic equations ('DAE'), and of delay differential equations. The functions provide an interface to the FORTRAN functions 'lsoda', 'lsodar', 'lsode', 'lsodes' of the 'ODEPACK' collection, to the FORTRAN functions 'dvode', 'zvode' and 'daspk' and a C-implementation of solvers of the 'Runge-Kutta' family with fixed or variable time steps. The package contains routines designed for solving 'ODEs' resulting from 1-D, 2-D and 3-D partial differential equations ('PDE') that have been converted to 'ODEs' by numerical differencing.

Maintained by Thomas Petzoldt. Last updated 1 years ago.

fortran openblas

37.6 match 12.33 score 8.0k scripts 427 dependents

sciml

diffeqr:Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)

An interface to 'DifferentialEquations.jl' <https://diffeq.sciml.ai/dev/> from the R programming language. It has unique high performance methods for solving ordinary differential equations (ODE), stochastic differential equations (SDE), delay differential equations (DDE), differential-algebraic equations (DAE), and more. Much of the functionality, including features like adaptive time stepping in SDEs, are unique and allow for multiple orders of magnitude speedup over more common methods. Supports GPUs, with support for CUDA (NVIDIA), AMD GPUs, Intel oneAPI GPUs, and Apple's Metal (M-series chip GPUs). 'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users. For more information, see Rackauckas and Nie (2017) <doi:10.5334/jors.151>.

Maintained by Christopher Rackauckas. Last updated 3 months ago.

dae dde delay-differential-equations differential-algebraic-equations differential-equations ode ordinary-differential-equations scientific-machine-learning sciml sde stochastic-differential-equations

52.2 match 143 stars 8.42 score 31 scripts

bioc

IgGeneUsage:Differential gene usage in immune repertoires

Detection of biases in the usage of immunoglobulin (Ig) genes is an important task in immune repertoire profiling. IgGeneUsage detects aberrant Ig gene usage between biological conditions using a probabilistic model which is analyzed computationally by Bayes inference. With this IgGeneUsage also avoids some common problems related to the current practice of null-hypothesis significance testing.

Maintained by Simo Kitanovski. Last updated 5 months ago.

differentialexpression regression genetics bayesian biomedicalinformatics immunooncology mathematicalbiology b-cell-receptor bcr-repertoire differential-analysis differential-gene-expression high-throughput-sequencing immune-repertoire immune-repertoire-analysis immune-repertoires immunogenomics immunoglobulin immunoinformatics immunological-bioinformatics immunology tcr-repertoire vdj-recombination cpp

64.3 match 6 stars 5.92 score 1 scripts

bioc

edgeR:Empirical Analysis of Digital Gene Expression Data in R

Differential expression analysis of sequence count data. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models, quasi-likelihood, and gene set enrichment. Can perform differential analyses of any type of omics data that produces read counts, including RNA-seq, ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral counts. RNA-seq analyses can be conducted at the gene or isoform level, and tests can be conducted for differential exon or transcript usage.

Maintained by Yunshun Chen. Last updated 5 days ago.

alternativesplicing batcheffect bayesian biomedicalinformatics cellbiology chipseq clustering coverage differentialexpression differentialmethylation differentialsplicing dnamethylation epigenetics functionalgenomics geneexpression genesetenrichment genetics immunooncology multiplecomparison normalization pathways proteomics qualitycontrol regression rnaseq sage sequencing singlecell systemsbiology timecourse transcription transcriptomics openblas

19.3 match 13.40 score 17k scripts 255 dependents

etiennebacher

flir:Find and Fix Lints in R Code

Lints are code patterns that are not optimal because they are inefficient, forget corner cases, or less readable. 'flir' provides a small set of functions to detect those lints and automatically fix them. It builds on 'astgrepr', which itself uses the Rust crate 'ast-grep' to parse and navigate R code.

Maintained by Etienne Bacher. Last updated 20 days ago.

44.3 match 52 stars 5.74 score 1 scripts

bioc

coRdon:Codon Usage Analysis and Prediction of Gene Expressivity

Tool for analysis of codon usage in various unannotated or KEGG/COG annotated DNA sequences. Calculates different measures of CU bias and CU-based predictors of gene expressivity, and performs gene set enrichment analysis for annotated sequences. Implements several methods for visualization of CU and enrichment analysis results.

Maintained by Anamaria Elek. Last updated 5 months ago.

software metagenomics geneexpression genesetenrichment geneprediction visualization kegg pathways genetics cellbiology biomedicalinformatics immunooncology

29.7 match 20 stars 7.71 score 48 scripts 1 dependents

bioc

miloR:Differential neighbourhood abundance testing on a graph

Milo performs single-cell differential abundance testing. Cell states are modelled as representative neighbourhoods on a nearest neighbour graph. Hypothesis testing is performed using either a negative bionomial generalized linear model or negative binomial generalized linear mixed model.

Maintained by Mike Morgan. Last updated 5 months ago.

singlecell multiplecomparison functionalgenomics software openblas cpp openmp

21.5 match 357 stars 10.49 score 340 scripts 1 dependents

jamesramsay5

fda:Functional Data Analysis

These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from <https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.

Maintained by James Ramsay. Last updated 4 months ago.

18.1 match 3 stars 12.29 score 2.0k scripts 143 dependents

eguidotti

calculus:High Dimensional Numerical and Symbolic Calculus

Efficient C++ optimized functions for numerical and symbolic calculus as described in Guidotti (2022) <doi:10.18637/jss.v104.i05>. It includes basic arithmetic, tensor calculus, Einstein summing convention, fast computation of the Levi-Civita symbol and generalized Kronecker delta, Taylor series expansion, multivariate Hermite polynomials, high-order derivatives, ordinary differential equations, differential operators (Gradient, Jacobian, Hessian, Divergence, Curl, Laplacian) and numerical integration in arbitrary orthogonal coordinate systems: cartesian, polar, spherical, cylindrical, parabolic or user defined by custom scale factors.

Maintained by Emanuele Guidotti. Last updated 2 years ago.

calculus coordinate-systems curl divergence einstein finite-difference gradient hermite hessian jacobian laplacian numerical-derivation numerical-derivatives numerical-differentiation symbolic-computation symbolic-differentiation taylor cpp

24.0 match 47 stars 8.92 score 66 scripts 7 dependents

cbiit

LDlinkR:Calculating Linkage Disequilibrium (LD) in Human Population Groups of Interest

Provides access to the 'LDlink' API (<https://ldlink.nih.gov/?tab=apiaccess>) using the R console. This programmatic access facilitates researchers who are interested in performing batch queries in 1000 Genomes Project (2015) <doi:10.1038/nature15393> data using 'LDlink'. 'LDlink' is an interactive and powerful suite of web-based tools for querying germline variants in human population groups of interest. For more details, please see Machiela et al. (2015) <doi:10.1093/bioinformatics/btv402>.

Maintained by Timothy A. Myers. Last updated 11 months ago.

ld-calculator ldlink ldlink-api ldlink-webtool linkage-disequilibrium population-genetics

23.1 match 58 stars 9.21 score 206 scripts 1 dependents

karlines

rootSolve:Nonlinear Root Finding, Equilibrium and Steady-State Analysis of Ordinary Differential Equations

Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). Includes routines that: (1) generate gradient and jacobian matrices (full and banded), (2) find roots of non-linear equations by the 'Newton-Raphson' method, (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the 'Newton-Raphson' method, or by dynamically running, (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations by numerical differencing (using the method-of-lines approach). Includes fortran code.

Maintained by Karline Soetaert. Last updated 1 years ago.

fortran

22.1 match 1 stars 9.61 score 1.2k scripts 216 dependents

bioc

condiments:Differential Topology, Progression and Differentiation

This package encapsulate many functions to conduct a differential topology analysis. It focuses on analyzing an 'omic dataset with multiple conditions. While the package is mostly geared toward scRNASeq, it does not place any restriction on the actual input format.

Maintained by Hector Roux de Bezieux. Last updated 3 months ago.

rnaseq sequencing software singlecell transcriptomics multiplecomparison visualization

31.5 match 26 stars 6.52 score 17 scripts

bioc

DEXSeq:Inference of differential exon usage in RNA-Seq

The package is focused on finding differential exon usage using RNA-seq exon counts between samples with different experimental designs. It provides functions that allows the user to make the necessary statistical tests based on a model that uses the negative binomial distribution to estimate the variance between biological replicates and generalized linear models for testing. The package also provides functions for the visualization and exploration of the results.

Maintained by Alejandro Reyes. Last updated 16 days ago.

immunooncology sequencing rnaseq differentialexpression alternativesplicing differentialsplicing geneexpression visualization

26.1 match 7.75 score 330 scripts 6 dependents

geobosh

Rdpack:Update and Manipulate Rd Documentation Objects

Functions for manipulation of R documentation objects, including functions reprompt() and ereprompt() for updating 'Rd' documentation for functions, methods and classes; 'Rd' macros for citations and import of references from 'bibtex' files for use in 'Rd' files and 'roxygen2' comments; 'Rd' macros for evaluating and inserting snippets of 'R' code and the results of its evaluation or creating graphics on the fly; and many functions for manipulation of references and Rd files.

Maintained by Georgi N. Boshnakov. Last updated 4 months ago.

bibtex bibtex-references citations documentation rd-format roxygen2

14.4 match 30 stars 13.58 score 73 scripts 2.3k dependents

bioc

methylKit:DNA methylation analysis from high-throughput bisulfite sequencing results

methylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from RRBS and its variants, but also target-capture methods and whole genome bisulfite sequencing. It also has functions to analyze base-pair resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq. Methylation calling can be performed directly from Bismark aligned BAM files.

Maintained by Altuna Akalin. Last updated 16 days ago.

dnamethylation sequencing methylseq genome-biology methylation statistical-analysis visualization curl bzip2 xz-utils zlib cpp

16.5 match 220 stars 11.80 score 578 scripts 3 dependents

brubinstein

diffpriv:Easy Differential Privacy

An implementation of major general-purpose mechanisms for privatizing statistics, models, and machine learners, within the framework of differential privacy of Dwork et al. (2006) <doi:10.1007/11681878_14>. Example mechanisms include the Laplace mechanism for releasing numeric aggregates, and the exponential mechanism for releasing set elements. A sensitivity sampler (Rubinstein & Alda, 2017) <arXiv:1706.02562> permits sampling target non-private function sensitivity; combined with the generic mechanisms, it permits turn-key privatization of arbitrary programs.

Maintained by Benjamin Rubinstein. Last updated 3 years ago.

data-science differential-privacy diffpriv machine-learning statistics

28.9 match 66 stars 6.54 score 52 scripts

bioc

psichomics:Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation

Interactive R package with an intuitive Shiny-based graphical interface for alternative splicing quantification and integrative analyses of alternative splicing and gene expression based on The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx), Sequence Read Archive (SRA) and user-provided data. The tool interactively performs survival, dimensionality reduction and median- and variance-based differential splicing and gene expression analyses that benefit from the incorporation of clinical and molecular sample-associated features (such as tumour stage or survival). Interactive visual access to genomic mapping and functional annotation of selected alternative splicing events is also included.

Maintained by Nuno Saraiva-Agostinho. Last updated 5 months ago.

sequencing rnaseq alternativesplicing differentialsplicing transcription gui principalcomponent survival biomedicalinformatics transcriptomics immunooncology visualization multiplecomparison geneexpression differentialexpression alternative-splicing bioconductor data-analyses differential-gene-expression differential-splicing-analysis gene-expression gtex recount2 rna-seq-data splicing-quantification sra tcga vast-tools cpp

26.8 match 36 stars 6.95 score 31 scripts

bioc

ASpli:Analysis of Alternative Splicing Using RNA-Seq

Integrative pipeline for the analysis of alternative splicing using RNAseq.

Maintained by Ariel Chernomoretz. Last updated 5 months ago.

immunooncology geneexpression transcription alternativesplicing coverage differentialexpression differentialsplicing timecourse rnaseq genomeannotation sequencing alignment

34.1 match 5.33 score 45 scripts 1 dependents

yuimaproject

yuima:The YUIMA Project Package for SDEs

Simulation and Inference for SDEs and Other Stochastic Processes.

Maintained by Stefano M. Iacus. Last updated 2 days ago.

openblas cpp

24.8 match 9 stars 7.26 score 92 scripts 2 dependents

bioc

diffcyt:Differential discovery in high-dimensional cytometry via high-resolution clustering

Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.

Maintained by Lukas M. Weber. Last updated 1 months ago.

immunooncology flowcytometry proteomics singlecell cellbasedassays cellbiology clustering featureextraction software

17.7 match 20 stars 9.98 score 225 scripts 5 dependents

bioc

TCGAbiolinks:TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

Maintained by Tiago Chedraoui Silva. Last updated 26 days ago.

dnamethylation differentialmethylation generegulation geneexpression methylationarray differentialexpression pathways network sequencing survival software bioc bioconductor gdc integrative-analysis tcga tcga-data tcgabiolinks

11.9 match 305 stars 14.45 score 1.6k scripts 6 dependents

bioc

dcanr:Differential co-expression/association network analysis

This package implements methods and an evaluation framework to infer differential co-expression/association networks. Various methods are implemented and can be evaluated using simulated datasets. Inference of differential co-expression networks can allow identification of networks that are altered between two conditions (e.g., health and disease).

Maintained by Dharmesh D. Bhuva. Last updated 5 months ago.

networkinference graphandnetwork differentialexpression network

22.4 match 6 stars 7.45 score 26 scripts 5 dependents

bioc

limma:Linear Models for Microarray and Omics Data

Data analysis, linear models and differential expression for omics data.

Maintained by Gordon Smyth. Last updated 5 days ago.

exonarray geneexpression transcription alternativesplicing differentialexpression differentialsplicing genesetenrichment dataimport bayesian clustering regression timecourse microarray micrornaarray mrnamicroarray onechannel proprietaryplatforms twochannel sequencing rnaseq batcheffect multiplecomparison normalization preprocessing qualitycontrol biomedicalinformatics cellbiology cheminformatics epigenetics functionalgenomics genetics immunooncology metabolomics proteomics systemsbiology transcriptomics

11.8 match 13.81 score 16k scripts 585 dependents

acguidoum

Sim.DiffProc:Simulation of Diffusion Processes

It provides users with a wide range of tools to simulate, estimate, analyze, and visualize the dynamics of stochastic differential systems in both forms Ito and Stratonovich. Statistical analysis with parallel Monte Carlo and moment equations methods of SDEs <doi:10.18637/jss.v096.i02>. Enabled many searchers in different domains to use these equations to modeling practical problems in financial and actuarial modeling and other areas of application, e.g., modeling and simulate of first passage time problem in shallow water using the attractive center (Boukhetala K, 1996) ISBN:1-56252-342-2.

Maintained by Arsalane Chouaib Guidoum. Last updated 1 years ago.

dynamic-system moment-equations monte-carlo-simulation parallel-computing stochastic-calculus stochastic-differential-equation transition-density

21.1 match 13 stars 7.69 score 86 scripts 4 dependents

bioc

tidytof:Analyze High-dimensional Cytometry Data Using Tidy Data Principles

This package implements an interactive, scientific analysis pipeline for high-dimensional cytometry data built using tidy data principles. It is specifically designed to play well with both the tidyverse and Bioconductor software ecosystems, with functionality for reading/writing data files, data cleaning, preprocessing, clustering, visualization, modeling, and other quality-of-life functions. tidytof implements a "grammar" of high-dimensional cytometry data analysis.

Maintained by Timothy Keyes. Last updated 5 months ago.

singlecell flowcytometry bioinformatics cytometry data-science single-cell tidyverse cpp

21.3 match 19 stars 7.26 score 35 scripts

mlampros

fastText:Efficient Learning of Word Representations and Sentence Classification

An interface to the 'fastText' <https://github.com/facebookresearch/fastText> library for efficient learning of word representations and sentence classification. The 'fastText' algorithm is explained in detail in (i) "Enriching Word Vectors with subword Information", Piotr Bojanowski, Edouard Grave, Armand Joulin, Tomas Mikolov, 2017, <doi:10.1162/tacl_a_00051>; (ii) "Bag of Tricks for Efficient Text Classification", Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov, 2017, <doi:10.18653/v1/e17-2068>; (iii) "FastText.zip: Compressing text classification models", Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Herve Jegou, Tomas Mikolov, 2016, <arXiv:1612.03651>.

Maintained by Lampros Mouselimis. Last updated 1 years ago.

cpp11 fasttext cpp

20.4 match 42 stars 7.37 score 56 scripts

enricoschumann

NMOF:Numerical Methods and Optimization in Finance

Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.

Maintained by Enrico Schumann. Last updated 30 days ago.

black-scholes differential-evolution genetic-algorithm grid-search heuristics implied-volatility local-search optimization particle-swarm-optimization simulated-annealing threshold-accepting

15.7 match 36 stars 9.56 score 101 scripts 4 dependents

ardiad

DEoptim:Global Optimization by Differential Evolution

Implements the Differential Evolution algorithm for global optimization of a real-valued function of a real-valued parameter vector as described in Mullen et al. (2011) <doi:10.18637/jss.v040.i06>.

Maintained by Katharine Mullen. Last updated 2 years ago.

differential-evolution evolutionary-algorithm global-optimization optimization

13.1 match 29 stars 11.42 score 680 scripts 124 dependents

bioc

DESeq2:Differential gene expression analysis based on the negative binomial distribution

Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

Maintained by Michael Love. Last updated 11 days ago.

sequencing rnaseq chipseq geneexpression transcription normalization differentialexpression bayesian regression principalcomponent clustering immunooncology openblas cpp

9.2 match 375 stars 16.11 score 17k scripts 115 dependents

bioc

methylSig:MethylSig: Differential Methylation Testing for WGBS and RRBS Data

MethylSig is a package for testing for differentially methylated cytosines (DMCs) or regions (DMRs) in whole-genome bisulfite sequencing (WGBS) or reduced representation bisulfite sequencing (RRBS) experiments. MethylSig uses a beta binomial model to test for significant differences between groups of samples. Several options exist for either site-specific or sliding window tests, and variance estimation.

Maintained by Raymond G. Cavalcante. Last updated 5 months ago.

dnamethylation differentialmethylation epigenetics regression methylseq differential-methylation dna-methylation

19.4 match 17 stars 7.37 score 23 scripts

bioc

ALDEx2:Analysis Of Differential Abundance Taking Sample and Scale Variation Into Account

A differential abundance analysis for the comparison of two or more conditions. Useful for analyzing data from standard RNA-seq or meta-RNA-seq assays as well as selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, optimized for three or more experimental replicates. The method infers biological and sampling variation to calculate the expected false discovery rate, given the variation, based on a Wilcoxon Rank Sum test and Welch's t-test (via aldex.ttest), a Kruskal-Wallis test (via aldex.kw), a generalized linear model (via aldex.glm), or a correlation test (via aldex.corr). All tests report predicted p-values and posterior Benjamini-Hochberg corrected p-values. ALDEx2 also calculates expected standardized effect sizes for paired or unpaired study designs. ALDEx2 can now be used to estimate the effect of scale on the results and report on the scale-dependent robustness of results.

Maintained by Greg Gloor. Last updated 5 months ago.

differentialexpression rnaseq transcriptomics geneexpression dnaseq chipseq bayesian sequencing software microbiome metagenomics immunooncology scale simulation posterior p-value

13.0 match 28 stars 10.70 score 424 scripts 3 dependents

mt1022

cubar:Codon Usage Bias Analysis

A suite of functions for rapid and flexible analysis of codon usage bias. It provides in-depth analysis at the codon level, including relative synonymous codon usage (RSCU), tRNA weight calculations, machine learning predictions for optimal or preferred codons, and visualization of codon-anticodon pairing. Additionally, it can calculate various gene- specific codon indices such as codon adaptation index (CAI), effective number of codons (ENC), fraction of optimal codons (Fop), tRNA adaptation index (tAI), mean codon stabilization coefficients (CSCg), and GC contents (GC/GC3s/GC4d). It also supports both standard and non-standard genetic code tables found in NCBI, as well as custom genetic code tables.

Maintained by Hong Zhang. Last updated 3 months ago.

bioinformatics codon-usage machine-learning sequence-analysis

22.3 match 6 stars 5.82 score 8 scripts

bioc

baySeq:Empirical Bayesian analysis of patterns of differential expression in count data

This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

Maintained by Samuel Granjeaud. Last updated 5 months ago.

sequencing differentialexpression multiplecomparison sage bayesian coverage

16.6 match 7.75 score 79 scripts 3 dependents

civisanalytics

civis:R Client for the 'Civis Platform API'

A convenient interface for making requests directly to the 'Civis Platform API' <https://www.civisanalytics.com/platform/>. Full documentation available 'here' <https://civisanalytics.github.io/civis-r/>.

Maintained by Peter Cooman. Last updated 2 months ago.

16.3 match 16 stars 7.84 score 144 scripts

bioc

tidybulk:Brings transcriptomics to the tidyverse

This is a collection of utility functions that allow to perform exploration of and calculations to RNA sequencing data, in a modular, pipe-friendly and tidy fashion.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics bioconductor bulk-transcriptional-analyses deseq2 differential-expression edger ensembl-ids entrez gene-symbols gsea mds-dimensions pca pipe redundancy tibble tidy tidy-data tidyverse transcripts tsne

13.4 match 168 stars 9.48 score 172 scripts 1 dependents

bioc

metagenomeSeq:Statistical analysis for sparse high-throughput sequencing

metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.

Maintained by Joseph N. Paulson. Last updated 3 months ago.

immunooncology classification clustering geneticvariability differentialexpression microbiome metagenomics normalization visualization multiplecomparison sequencing software

10.3 match 69 stars 12.02 score 494 scripts 7 dependents

bioc

TOAST:Tools for the analysis of heterogeneous tissues

This package is devoted to analyzing high-throughput data (e.g. gene expression microarray, DNA methylation microarray, RNA-seq) from complex tissues. Current functionalities include 1. detect cell-type specific or cross-cell type differential signals 2. tree-based differential analysis 3. improve variable selection in reference-free deconvolution 4. partial reference-free deconvolution with prior knowledge.

Maintained by Ziyi Li. Last updated 5 months ago.

dnamethylation geneexpression differentialexpression differentialmethylation microarray genetarget epigenetics methylationarray

15.2 match 11 stars 8.01 score 104 scripts 3 dependents

bioc

DiffBind:Differential Binding Analysis of ChIP-Seq Peak Data

Compute differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions.

Maintained by Rory Stark. Last updated 2 months ago.

sequencing chipseq atacseq dnaseseq methylseq ripseq differentialpeakcalling differentialmethylation generegulation histonemodification peakdetection biomedicalinformatics cellbiology multiplecomparison normalization reportwriting epigenetics functionalgenomics curl bzip2 xz-utils zlib cpp

16.6 match 7.13 score 512 scripts 2 dependents

bioc

ChromSCape:Analysis of single-cell epigenomics datasets with a Shiny App

ChromSCape - Chromatin landscape profiling for Single Cells - is a ready-to-launch user-friendly Shiny Application for the analysis of single-cell epigenomics datasets (scChIP-seq, scATAC-seq, scCUT&Tag, ...) from aligned data to differential analysis & gene set enrichment analysis. It is highly interactive, enables users to save their analysis and covers a wide range of analytical steps: QC, preprocessing, filtering, batch correction, dimensionality reduction, vizualisation, clustering, differential analysis and gene set analysis.

Maintained by Pacome Prompsy. Last updated 5 months ago.

shinyapps software singlecell chipseq atacseq methylseq classification clustering epigenetics principalcomponent annotation batcheffect multiplecomparison normalization pathways preprocessing qualitycontrol reportwriting visualization genesetenrichment differentialpeakcalling epigenomics shiny single-cell cpp

20.3 match 14 stars 5.83 score 16 scripts

bioc

DRIMSeq:Differential transcript usage and tuQTL analyses with Dirichlet-multinomial model in RNA-seq

The package provides two frameworks. One for the differential transcript usage analysis between different conditions and one for the tuQTL analysis. Both are based on modeling the counts of genomic features (i.e., transcripts) with the Dirichlet-multinomial distribution. The package also makes available functions for visualization and exploration of the data and results.

Maintained by Malgorzata Nowicka. Last updated 5 months ago.

immunooncology snp alternativesplicing differentialsplicing genetics rnaseq sequencing workflowstep multiplecomparison geneexpression differentialexpression

17.1 match 6.91 score 136 scripts 2 dependents

bioc

gemma.R:A wrapper for Gemma's Restful API to access curated gene expression data and differential expression analyses

Low- and high-level wrappers for Gemma's RESTful API. They enable access to curated expression and differential expression data from over 10,000 published studies. Gemma is a web site, database and a set of tools for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles.

Maintained by Ogan Mancarci. Last updated 4 months ago.

software dataimport microarray singlecell thirdpartyclient differentialexpression geneexpression bayesian annotation experimentaldesign normalization batcheffect preprocessing bioinformatics gemma genomics transcriptomics

15.5 match 10 stars 7.57 score 26 scripts

cran

MARVEL:Revealing Splicing Dynamics at Single-Cell Resolution

Alternative splicing represents an additional and underappreciated layer of complexity underlying gene expression profiles. Nevertheless, there remains hitherto a paucity of software to investigate splicing dynamics at single-cell resolution. 'MARVEL' enables splicing analysis of single-cell RNA-sequencing data generated from plate- and droplet-based library preparation methods.

Maintained by Sean Wen. Last updated 2 years ago.

42.3 match 2.71 score 51 scripts

bioc

projectR:Functions for the projection of weights from PCA, CoGAPS, NMF, correlation, and clustering

Functions for the projection of data into the spaces defined by PCA, CoGAPS, NMF, correlation, and clustering.

Maintained by Genevieve Stein-OBrien. Last updated 5 months ago.

functionalprediction generegulation biologicalquestion software

13.8 match 62 stars 8.11 score 70 scripts

bioc

singleCellTK:Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

The Single Cell Toolkit (SCTK) in the singleCellTK package provides an interface to popular tools for importing, quality control, analysis, and visualization of single cell RNA-seq data. SCTK allows users to seamlessly integrate tools from various packages at different stages of the analysis workflow. A general "a la carte" workflow gives users the ability access to multiple methods for data importing, calculation of general QC metrics, doublet detection, ambient RNA estimation and removal, filtering, normalization, batch correction or integration, dimensionality reduction, 2-D embedding, clustering, marker detection, differential expression, cell type labeling, pathway analysis, and data exporting. Curated workflows can be used to run Seurat and Celda. Streamlined quality control can be performed on the command line using the SCTK-QC pipeline. Users can analyze their data using commands in the R console or by using an interactive Shiny Graphical User Interface (GUI). Specific analyses or entire workflows can be summarized and shared with comprehensive HTML reports generated by Rmarkdown. Additional documentation and vignettes can be found at camplab.net/sctk.

Maintained by Joshua David Campbell. Last updated 23 days ago.

singlecell geneexpression differentialexpression alignment clustering immunooncology batcheffect normalization qualitycontrol dataimport gui

11.0 match 181 stars 10.16 score 252 scripts

bioc

bandle:An R package for the Bayesian analysis of differential subcellular localisation experiments

The Bandle package enables the analysis and visualisation of differential localisation experiments using mass-spectrometry data. Experimental methods supported include dynamic LOPIT-DC, hyperLOPIT, Dynamic Organellar Maps, Dynamic PCP. It provides Bioconductor infrastructure to analyse these data.

Maintained by Oliver M. Crook. Last updated 2 months ago.

bayesian classification clustering immunooncology qualitycontrol dataimport proteomics massspectrometry openblas cpp openmp

20.0 match 4 stars 5.56 score 3 scripts

bioc

SeqGSEA:Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing

The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively.

Maintained by Xi Wang. Last updated 5 months ago.

sequencing rnaseq genesetenrichment geneexpression differentialexpression differentialsplicing immunooncology

25.4 match 4.34 score 11 scripts

bioc

ideal:Interactive Differential Expression AnaLysis

This package provides functions for an Interactive Differential Expression AnaLysis of RNA-sequencing datasets, to extract quickly and effectively information downstream the step of differential expression. A Shiny application encapsulates the whole package. Support for reproducibility of the whole analysis is provided by means of a template report which gets automatically compiled and can be stored/shared.

Maintained by Federico Marini. Last updated 3 months ago.

immunooncology geneexpression differentialexpression rnaseq sequencing visualization qualitycontrol gui genesetenrichment reportwriting shinyapps bioconductor differential-expression reproducible-research rna-seq rna-seq-analysis shiny user-friendly

16.2 match 29 stars 6.78 score 5 scripts

bioc

tradeSeq:trajectory-based differential expression analysis for sequencing data

tradeSeq provides a flexible method for fitting regression models that can be used to find genes that are differentially expressed along one or multiple lineages in a trajectory. Based on the fitted models, it uses a variety of tests suited to answer different questions of interest, e.g. the discovery of genes for which expression is associated with pseudotime, or which are differentially expressed (in a specific region) along the trajectory. It fits a negative binomial generalized additive model (GAM) for each gene, and performs inference on the parameters of the GAM.

Maintained by Hector Roux de Bezieux. Last updated 5 months ago.

clustering regression timecourse differentialexpression geneexpression rnaseq sequencing software singlecell transcriptomics multiplecomparison visualization

10.9 match 247 stars 10.06 score 440 scripts

traitecoevo

hmde:Hierarchical Methods for Differential Equations

Wrapper for Stan that offers a number of in-built models to implement a hierarchical Bayesian longitudinal model for repeat observation data. Model choice selects the differential equation that is fit to the observations. Single and multi-individual models are available.

Maintained by Tess OBrien. Last updated 1 months ago.

bayesian-inverse-problems bayesian-methods differential-equations hierarchical-models rstan stan cpp

19.4 match 3 stars 5.53 score 10 scripts

bioc

diffUTR:diffUTR: Streamlining differential exon and 3' UTR usage

The diffUTR package provides a uniform interface and plotting functions for limma/edgeR/DEXSeq -powered differential bin/exon usage. It includes in addition an improved version of the limma::diffSplice method. Most importantly, diffUTR further extends the application of these frameworks to differential UTR usage analysis using poly-A site databases.

Maintained by Pierre-Luc Germain. Last updated 5 months ago.

geneexpression

20.0 match 6 stars 5.38 score 9 scripts

bioc

DEP:Differential Enrichment analysis of Proteomics data

This package provides an integrated analysis workflow for robust and reproducible analysis of mass spectrometry proteomics data for differential protein expression or differential enrichment. It requires tabular input (e.g. txt files) as generated by quantitative analysis softwares of raw mass spectrometry data, such as MaxQuant or IsobarQuant. Functions are provided for data preparation, filtering, variance normalization and imputation of missing values, as well as statistical testing of differentially enriched / expressed proteins. It also includes tools to check intermediate steps in the workflow, such as normalization and missing values imputation. Finally, visualization tools are provided to explore the results, including heatmap, volcano plot and barplot representations. For scientists with limited experience in R, the package also contains wrapper functions that entail the complete analysis workflow and generate a report. Even easier to use are the interactive Shiny apps that are provided by the package.

Maintained by Arne Smits. Last updated 5 months ago.

immunooncology proteomics massspectrometry differentialexpression datarepresentation

15.0 match 7.10 score 628 scripts

bioc

waddR:Statistical tests for detecting differential distributions based on the 2-Wasserstein distance

The package offers statistical tests based on the 2-Wasserstein distance for detecting and characterizing differences between two distributions given in the form of samples. Functions for calculating the 2-Wasserstein distance and testing for differential distributions are provided, as well as a specifically tailored test for differential expression in single-cell RNA sequencing data.

Maintained by Julian Flesch. Last updated 5 months ago.

software statisticalmethod singlecell differentialexpression cpp

15.8 match 25 stars 6.70 score 6 scripts

sgsokol

Deriv:Symbolic Differentiation

R-based solution for symbolic differentiation. It admits user-defined function as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.

Maintained by Serguei Sokol. Last updated 6 months ago.

8.7 match 39 stars 12.05 score 334 scripts 1.0k dependents

murrayefford

secr:Spatially Explicit Capture-Recapture

Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

Maintained by Murray Efford. Last updated 2 days ago.

cpp

10.1 match 3 stars 10.18 score 410 scripts 5 dependents

bioc

DEGreport:Report of DEG analysis

Creation of ready-to-share figures of differential expression analyses of count data. It integrates some of the code mentioned in DESeq2 and edgeR vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene.

Maintained by Lorena Pantano. Last updated 5 months ago.

differentialexpression visualization rnaseq reportwriting geneexpression immunooncology bioconductor differential-expression qc report rna-seq smallrna

10.9 match 24 stars 9.42 score 354 scripts 1 dependents

daqana

dqrng:Fast Pseudo Random Number Generators

Several fast random number generators are provided as C++ header only libraries: The PCG family by O'Neill (2014 <https://www.cs.hmc.edu/tr/hmc-cs-2014-0905.pdf>) as well as the Xoroshiro / Xoshiro family by Blackman and Vigna (2021 <doi:10.1145/3460772>). In addition fast functions for generating random numbers according to a uniform, normal and exponential distribution are included. The latter two use the Ziggurat algorithm originally proposed by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>). The fast sampling methods support unweighted sampling both with and without replacement. These functions are exported to R and as a C++ interface and are enabled for use with the default 64 bit generator from the PCG family, Xoroshiro128+/++/** and Xoshiro256+/++/** as well as the 64 bit version of the 20 rounds Threefry engine (Salmon et al., 2011, <doi:10.1145/2063384.2063405>) as provided by the package 'sitmo'.

Maintained by Ralf Stubner. Last updated 6 months ago.

random random-distributions random-generation random-sampling rng cpp

7.7 match 42 stars 13.12 score 188 scripts 183 dependents

bioc

ballgown:Flexible, isoform-level differential expression analysis

Tools for statistical analysis of assembled transcriptomes, including flexible differential expression analysis, visualization of transcript structures, and matching of assembled transcripts to annotation.

Maintained by Jack Fu. Last updated 5 months ago.

immunooncology rnaseq statisticalmethod preprocessing differentialexpression

9.4 match 146 stars 10.51 score 338 scripts 1 dependents

bioc

zinbwave:Zero-Inflated Negative Binomial Model for RNA-Seq Data

Implements a general and flexible zero-inflated negative binomial model that can be used to provide a low-dimensional representations of single-cell RNA-seq data. The model accounts for zero inflation (dropouts), over-dispersion, and the count nature of the data. The model also accounts for the difference in library sizes and optionally for batch effects and/or other covariates, avoiding the need for pre-normalize the data.

Maintained by Davide Risso. Last updated 5 months ago.

immunooncology dimensionreduction geneexpression rnaseq software transcriptomics sequencing singlecell

9.4 match 43 stars 10.53 score 190 scripts 6 dependents

bioc

dreamlet:Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs

Recent advances in single cell/nucleus transcriptomic technology has enabled collection of cohort-scale datasets to study cell type specific gene expression differences associated disease state, stimulus, and genetic regulation. The scale of these data, complex study designs, and low read count per cell mean that characterizing cell type specific molecular mechanisms requires a user-frieldly, purpose-build analytical framework. We have developed the dreamlet package that applies a pseudobulk approach and fits a regression model for each gene and cell cluster to test differential expression across individuals associated with a trait of interest. Use of precision-weighted linear mixed models enables accounting for repeated measures study designs, high dimensional batch effects, and varying sequencing depth or observed cells per biosample.

Maintained by Gabriel Hoffman. Last updated 5 months ago.

rnaseq geneexpression differentialexpression batcheffect qualitycontrol regression genesetenrichment generegulation epigenetics functionalgenomics transcriptomics normalization singlecell preprocessing sequencing immunooncology software cpp

12.1 match 12 stars 8.09 score 128 scripts

mrkaye97

slackr:Send Messages, Images, R Objects and Files to 'Slack' Channels/Users

'Slack' <https://slack.com/> provides a service for teams to collaborate by sharing messages, images, links, files and more. Functions are provided that make it possible to interact with the 'Slack' platform 'API'. When you need to share information or data from R, rather than resort to copy/ paste in e-mails or other services like 'Skype' <https://www.skype.com/en/>, you can use this package to send well-formatted output from multiple R objects and expressions to all teammates at the same time with little effort. You can also send images from the current graphics device, R objects, and upload files.

Maintained by Matt Kaye. Last updated 5 months ago.

slack

8.3 match 306 stars 11.66 score 179 scripts

cbielow

PTXQC:Quality Report Generation for MaxQuant and mzTab Results

Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite (from .txt files) or mzTab files (ideally from OpenMS 'QualityControl' tool). Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) <doi:10.1021/acs.jproteome.5b00780>.

Maintained by Chris Bielow. Last updated 1 years ago.

drag-and-drop hacktoberfest heatmap match-between-runs maxquant metric mztab openms proteomics quality-control quality-metrics report

10.2 match 42 stars 9.35 score 105 scripts 1 dependents

jgx65

hierfstat:Estimation and Tests of Hierarchical F-Statistics

Estimates hierarchical F-statistics from haploid or diploid genetic data with any numbers of levels in the hierarchy, following the algorithm of Yang (Evolution(1998), 52:950). Tests via randomisations the significance of each F and variance components, using the likelihood-ratio statistics G (Goudet et al. (1996) <https://academic.oup.com/genetics/article/144/4/1933/6017091>). Estimates genetic diversity statistics for haploid and diploid genetic datasets in various formats, including inbreeding and coancestry coefficients, and population specific F-statistics following Weir and Goudet (2017) <https://academic.oup.com/genetics/article/206/4/2085/6072590>.

Maintained by Jerome Goudet. Last updated 4 months ago.

devtools fstatistics gwas hierfstat kinship population-genetics population-genomics quantitative-genetics simulations

8.7 match 25 stars 10.94 score 560 scripts 4 dependents

bioc

SynMut:SynMut: Designing Synonymously Mutated Sequences with Different Genomic Signatures

There are increasing demands on designing virus mutants with specific dinucleotide or codon composition. This tool can take both dinucleotide preference and/or codon usage bias into account while designing mutants. It is a powerful tool for in silico designs of DNA sequence mutants.

Maintained by Haogao Gu. Last updated 5 months ago.

sequencematching experimentaldesign preprocessing

22.0 match 2 stars 4.30 score 1 scripts

oobianom

quickcode:Quick and Essential 'R' Tricks for Better Scripts

The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to improve your scripts. Improve the quality and reproducibility of 'R' scripts.

Maintained by Obinna Obianom. Last updated 13 days ago.

colors data distributions images

12.2 match 5 stars 7.76 score 7 scripts 6 dependents

kfarleigh

PopGenHelpR:Streamline Population Genomic and Genetic Analyses

Estimate commonly used population genomic statistics and generate publication quality figures. 'PopGenHelpR' uses vcf, 'geno' (012), and csv files to generate output.

Maintained by Keaka Farleigh. Last updated 8 months ago.

diversity fst heterozygosity interpolation neis population-genetics population-genomics private-alleles snmf structure vcf

18.0 match 3 stars 5.17 score 14 scripts

bioc

fishpond:Fishpond: downstream methods and tools for expression data

Fishpond contains methods for differential transcript and gene expression analysis of RNA-seq data using inferential replicates for uncertainty of abundance quantification, as generated by Gibbs sampling or bootstrap sampling. Also the package contains a number of utilities for working with Salmon and Alevin quantification files.

Maintained by Michael Love. Last updated 5 months ago.

sequencing rnaseq geneexpression transcription normalization regression multiplecomparison batcheffect visualization differentialexpression differentialsplicing alternativesplicing singlecell bioconductor gene-expression genomics salmon scrnaseq statistics transcriptomics

11.8 match 28 stars 7.83 score 150 scripts

bioc

ANCOMBC:Microbiome differential abudance and correlation analyses with bias correction

ANCOMBC is a package containing differential abundance (DA) and correlation analyses for microbiome data. Specifically, the package includes Analysis of Compositions of Microbiomes with Bias Correction 2 (ANCOM-BC2), Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC), and Analysis of Composition of Microbiomes (ANCOM) for DA analysis, and Sparse Estimation of Correlations among Microbiomes (SECOM) for correlation analysis. Microbiome data are typically subject to two sources of biases: unequal sampling fractions (sample-specific biases) and differential sequencing efficiencies (taxon-specific biases). Methodologies included in the ANCOMBC package are designed to correct these biases and construct statistically consistent estimators.

Maintained by Huang Lin. Last updated 2 months ago.

differentialexpression microbiome normalization sequencing software ancom ancombc ancombc2 correlation differential-abundance-analysis secom

10.3 match 119 stars 8.97 score 406 scripts 1 dependents

bioc

missMethyl:Analysing Illumina HumanMethylation BeadChip Data

Normalisation, testing for differential variability and differential methylation and gene set testing for data from Illumina's Infinium HumanMethylation arrays. The normalisation procedure is subset-quantile within-array normalisation (SWAN), which allows Infinium I and II type probes on a single array to be normalised together. The test for differential variability is based on an empirical Bayes version of Levene's test. Differential methylation testing is performed using RUV, which can adjust for systematic errors of unknown origin in high-dimensional data by using negative control probes. Gene ontology analysis is performed by taking into account the number of probes per gene on the array, as well as taking into account multi-gene associated probes.

Maintained by Belinda Phipson. Last updated 13 days ago.

normalization dnamethylation methylationarray genomicvariation geneticvariability differentialmethylation genesetenrichment

12.7 match 7.24 score 300 scripts 1 dependents

bioc

muscat:Multi-sample multi-group scRNA-seq data analysis tools

`muscat` provides various methods and visualization tools for DS analysis in multi-sample, multi-group, multi-(cell-)subpopulation scRNA-seq data, including cell-level mixed models and methods based on aggregated “pseudobulk” data, as well as a flexible simulation platform that mimics both single and multi-sample scRNA-seq data.

Maintained by Helena L. Crowell. Last updated 5 months ago.

immunooncology differentialexpression sequencing singlecell software statisticalmethod visualization

9.0 match 181 stars 10.26 score 686 scripts

philchalmers

mirt:Multidimensional Item Response Theory

Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.

Maintained by Phil Chalmers. Last updated 11 days ago.

irt mirt openblas cpp openmp

6.1 match 210 stars 14.98 score 2.5k scripts 40 dependents

hopkinsidd

phylosamp:Sample Size Calculations for Molecular and Phylogenetic Studies

Implements novel tools for estimating sample sizes needed for phylogenetic studies, including studies focused on estimating the probability of true pathogen transmission between two cases given phylogenetic linkage and studies focused on tracking pathogen variants at a population level. Methods described in Wohl, Giles, and Lessler (2021) and in Wohl, Lee, DiPrete, and Lessler (2023).

Maintained by Justin Lessler. Last updated 2 years ago.

phylogenetics sampling

13.6 match 12 stars 6.65 score 25 scripts

sssydysss

TransProR:Analysis and Visualization of Multi-Omics Data

A tool for comprehensive transcriptomic data analysis, with a focus on transcript-level data preprocessing, expression profiling, differential expression analysis, and functional enrichment. It enables researchers to identify key biological processes, disease biomarkers, and gene regulatory mechanisms. 'TransProR' is aimed at researchers and bioinformaticians working with RNA-Seq data, providing an intuitive framework for in-depth analysis and visualization of transcriptomic datasets. The package includes comprehensive documentation and usage examples to guide users through the entire analysis pipeline. The differential expression analysis methods incorporated in the package include 'limma' (Ritchie et al., 2015, <doi:10.1093/nar/gkv007>; Smyth, 2005, <doi:10.1007/0-387-29362-0_23>), 'edgeR' (Robinson et al., 2010, <doi:10.1093/bioinformatics/btp616>), 'DESeq2' (Love et al., 2014, <doi:10.1186/s13059-014-0550-8>), and Wilcoxon tests (Li et al., 2022, <doi:10.1186/s13059-022-02648-4>), providing flexible and robust approaches to RNA-Seq data analysis. For more information, refer to the package vignettes and related publications.

Maintained by Dongyue Yu. Last updated 19 days ago.

11.8 match 174 stars 7.55 score 34 scripts

kingaa

pomp:Statistical Inference for Partially Observed Markov Processes

Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.

Maintained by Aaron A. King. Last updated 1 months ago.

abc b-spline differential-equations dynamical-systems iterated-filtering likelihood likelihood-free markov-chain-monte-carlo markov-model mathematical-modelling measurement-error particle-filter sequential-monte-carlo simulation-based-inference sobol-sequence state-space statistical-inference stochastic-processes time-series openblas

7.5 match 115 stars 11.81 score 1.3k scripts 4 dependents

bioc

monocle:Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Monocle performs differential expression and time-series analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle also performs differential expression analysis, clustering, visualization, and other useful tasks on single cell expression data. It is designed to work with RNA-Seq and qPCR data, but could be used with other types as well.

Maintained by Cole Trapnell. Last updated 5 months ago.

immunooncology sequencing rnaseq geneexpression differentialexpression infrastructure dataimport datarepresentation visualization clustering multiplecomparison qualitycontrol cpp

9.9 match 8.89 score 1.6k scripts 2 dependents

katrionagoldmann

volcano3D:3D Volcano Plots and Polar Plots for Three-Class Data

Generates interactive plots for analysing and visualising three-class high dimensional data. It is particularly suited to visualising differences in continuous attributes such as gene/protein/biomarker expression levels between three groups. Differential gene/biomarker expression analysis between two classes is typically shown as a volcano plot. However, with three groups this type of visualisation is particularly difficult to interpret. This package generates 3D volcano plots and 3-way polar plots for easier interpretation of three-class data.

Maintained by Katriona Goldmann. Last updated 2 years ago.

bioinformatics differential-expression differential-expression-analysis gene-expression interactive omics plotly rna-seq transcriptomics volcanoplots

14.7 match 36 stars 5.90 score 37 scripts

dwinter

mmod:Modern Measures of Population Differentiation

Provides functions for measuring population divergence from genotypic data.

Maintained by David Winter. Last updated 8 years ago.

10.5 match 11 stars 8.25 score 116 scripts 2 dependents

projectmosaic

mosaicCalc:R-Language Based Calculus Operations for Teaching

Software to support the introductory *MOSAIC Calculus* textbook <https://www.mosaic-web.org/MOSAIC-Calculus/>), one of many data- and modeling-oriented educational resources developed by Project MOSAIC (<https://www.mosaic-web.org/>). Provides symbolic and numerical differentiation and integration, as well as support for applied linear algebra (for data science), and differential equations/dynamics. Includes grammar-of-graphics-based functions for drawing vector fields, trajectories, etc. The software is suitable for general use, but intended mainly for teaching calculus.

Maintained by Daniel Kaplan. Last updated 20 days ago.

9.9 match 13 stars 8.68 score 546 scripts

aggregate-genius

periscope2:Enterprise Streamlined 'shiny' Application Framework Using 'bs4Dash'

A framework for building enterprise, scalable and UI-standardized 'shiny' applications. It brings enhanced features such as 'bootstrap' v4 <https://getbootstrap.com/docs/4.0/getting-started/introduction/>, additional and enhanced 'shiny' modules, customizable UI features, as well as an enhanced application file organization paradigm. This update allows developers to harness the ability to build powerful applications and enriches the 'shiny' developers' experience when building and maintaining applications.

Maintained by Mohammed Ali. Last updated 2 months ago.

periscope shiny

13.3 match 9 stars 6.49 score 34 scripts

bioc

satuRn:Scalable Analysis of Differential Transcript Usage for Bulk and Single-Cell RNA-sequencing Applications

satuRn provides a higly performant and scalable framework for performing differential transcript usage analyses. The package consists of three main functions. The first function, fitDTU, fits quasi-binomial generalized linear models that model transcript usage in different groups of interest. The second function, testDTU, tests for differential usage of transcripts between groups of interest. Finally, plotDTU visualizes the usage profiles of transcripts in groups of interest.

Maintained by Jeroen Gilis. Last updated 5 months ago.

regression experimentaldesign differentialexpression geneexpression rnaseq sequencing software singlecell transcriptomics multiplecomparison visualization

12.3 match 21 stars 6.97 score 74 scripts 1 dependents

r-lib

ps:List, Query, Manipulate System Processes

List, query and manipulate all system processes, on 'Windows', 'Linux' and 'macOS'.

Maintained by Gábor Csárdi. Last updated 16 days ago.

5.7 match 79 stars 15.09 score 108 scripts 1.5k dependents

bioc

MicrobiotaProcess:A comprehensive R package for managing and analyzing microbiome and other ecological data within the tidy framework

MicrobiotaProcess is an R package for analysis, visualization and biomarker discovery of microbial datasets. It introduces MPSE class, this make it more interoperable with the existing computing ecosystem. Moreover, it introduces a tidy microbiome data structure paradigm and analysis grammar. It provides a wide variety of microbiome data analysis procedures under the unified and common framework (tidy-like framework).

Maintained by Shuangbin Xu. Last updated 5 months ago.

visualization microbiome software multiplecomparison featureextraction microbiome-analysis microbiome-data

8.7 match 183 stars 9.70 score 126 scripts 1 dependents

sgiddens

DPpack:Differentially Private Statistical Analysis and Machine Learning

An implementation of common statistical analysis and models with differential privacy (Dwork et al., 2006a) <doi:10.1007/11681878_14> guarantees. The package contains, for example, functions providing differentially private computations of mean, variance, median, histograms, and contingency tables. It also implements some statistical models and machine learning algorithms such as linear regression (Kifer et al., 2012) <https://proceedings.mlr.press/v23/kifer12.html> and SVM (Chaudhuri et al., 2011) <https://jmlr.org/papers/v12/chaudhuri11a.html>. In addition, it implements some popular randomization mechanisms, including the Laplace mechanism (Dwork et al., 2006a) <doi:10.1007/11681878_14>, Gaussian mechanism (Dwork et al., 2006b) <doi:10.1007/11761679_29>, analytic Gaussian mechanism (Balle & Wang, 2018) <https://proceedings.mlr.press/v80/balle18a.html>, and exponential mechanism (McSherry & Talwar, 2007) <doi:10.1109/FOCS.2007.66>.

Maintained by Spencer Giddens. Last updated 5 months ago.

23.2 match 3 stars 3.65 score 3 scripts

bioc

DAPAR:Tools for the Differential Analysis of Proteins Abundance with R

The package DAPAR is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required (see `Prostar` package).

Maintained by Samuel Wieczorek. Last updated 5 months ago.

proteomics normalization preprocessing massspectrometry qualitycontrol go dataimport prostar1

15.6 match 2 stars 5.42 score 22 scripts 1 dependents

cdriveraus

ctsem:Continuous Time Structural Equation Modelling

Hierarchical continuous (and discrete) time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE) or difference equation, measurement models are typically multivariate normal factor models. Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default. Nonlinearities, (state dependent parameters) and random effects on all parameters are possible, using either max likelihood / max a posteriori optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf> for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>. Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> . Stan based functions are not available on 32 bit Windows systems at present. <https://cdriver.netlify.app/> contains some tutorial blog posts.

Maintained by Charles Driver. Last updated 11 days ago.

stochastic-differential-equations time-series cpp

8.8 match 42 stars 9.58 score 366 scripts 1 dependents

rstudio

keras3:R Interface to 'Keras'

Interface to 'Keras' <https://keras.io>, a high-level neural networks API. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.

Maintained by Tomasz Kalinowski. Last updated 4 days ago.

6.2 match 845 stars 13.57 score 264 scripts 2 dependents

bioc

INDEED:Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection Package

An R package for integrated differential expression and differential network analysis based on omic data for cancer biomarker discovery. Both correlation and partial correlation can be used to generate differential network to aid the traditional differential expression analysis to identify changes between biomolecules on both their expression and pairwise association levels. A detailed description of the methodology has been published in Methods journal (PMID: 27592383). An interactive visualization feature allows for the exploration and selection of candidate biomarkers.

Maintained by Ressom group. Last updated 5 months ago.

immunooncology software researchfield biologicalquestion statisticalmethod differentialexpression massspectrometry metabolomics

14.1 match 4 stars 5.92 score 10 scripts

bioc

UMI4Cats:UMI4Cats: Processing, analysis and visualization of UMI-4C chromatin contact data

UMI-4C is a technique that allows characterization of 3D chromatin interactions with a bait of interest, taking advantage of a sonication step to produce unique molecular identifiers (UMIs) that help remove duplication bias, thus allowing a better differential comparsion of chromatin interactions between conditions. This package allows processing of UMI-4C data, starting from FastQ files provided by the sequencing facility. It provides two statistical methods for detecting differential contacts and includes a visualization function to plot integrated information from a UMI-4C assay.

Maintained by Mireia Ramos-Rodriguez. Last updated 5 months ago.

qualitycontrol preprocessing alignment normalization visualization sequencing coverage chromatin chromatin-interaction genomics umi4c

14.9 match 5 stars 5.57 score 7 scripts

bioc

InPAS:Identify Novel Alternative PolyAdenylation Sites (PAS) from RNA-seq data

Alternative polyadenylation (APA) is one of the important post- transcriptional regulation mechanisms which occurs in most human genes. InPAS facilitates the discovery of novel APA sites and the differential usage of APA sites from RNA-Seq data. It leverages cleanUpdTSeq to fine tune identified APA sites by removing false sites.

Maintained by Jianhong Ou. Last updated 2 months ago.

alternative polyadenylation differential polyadenylation site usage rna-seq gene regulation transcription

19.3 match 4.30 score 1 scripts

bioc

CATALYST:Cytometry dATa anALYSis Tools

CATALYST provides tools for preprocessing of and differential discovery in cytometry data such as FACS, CyTOF, and IMC. Preprocessing includes i) normalization using bead standards, ii) single-cell deconvolution, and iii) bead-based compensation. For differential discovery, the package provides a number of convenient functions for data processing (e.g., clustering, dimension reduction), as well as a suite of visualizations for exploratory data analysis and exploration of results from differential abundance (DA) and state (DS) analysis in order to identify differences in composition and expression profiles at the subpopulation-level, respectively.

Maintained by Helena L. Crowell. Last updated 4 months ago.

clustering dataimport differentialexpression experimentaldesign flowcytometry immunooncology massspectrometry normalization preprocessing singlecell software statisticalmethod visualization

7.5 match 67 stars 11.06 score 362 scripts 2 dependents

bioc

vidger:Create rapid visualizations of RNAseq data in R

The aim of vidger is to rapidly generate information-rich visualizations for the interpretation of differential gene expression results from three widely-used tools: Cuffdiff, DESeq2, and edgeR.

Maintained by Brandon Monier. Last updated 5 months ago.

immunooncology visualization rnaseq differentialexpression geneexpression data-munging differential-expression gene-expression rna-seq-analysis

12.3 match 19 stars 6.61 score 27 scripts

bioc

glmGamPoi:Fit a Gamma-Poisson Generalized Linear Model

Fit linear models to overdispersed count data. The package can estimate the overdispersion and fit repeated models for matrix input. It is designed to handle large input datasets as they typically occur in single cell RNA-seq experiments.

Maintained by Constantin Ahlmann-Eltze. Last updated 1 months ago.

regression rnaseq software singlecell gamma-poisson glm negative-binomial-regression on-disk openblas cpp

6.7 match 110 stars 12.11 score 1.0k scripts 4 dependents

bioc

cTRAP:Identification of candidate causal perturbations from differential gene expression data

Compare differential gene expression results with those from known cellular perturbations (such as gene knock-down, overexpression or small molecules) derived from the Connectivity Map. Such analyses allow not only to infer the molecular causes of the observed difference in gene expression but also to identify small molecules that could drive or revert specific transcriptomic alterations.

Maintained by Nuno Saraiva-Agostinho. Last updated 5 months ago.

differentialexpression geneexpression rnaseq transcriptomics pathways immunooncology genesetenrichment bioconductor bioinformatics cmap gene-expression l1000

15.8 match 5 stars 5.08 score 16 scripts

bioc

dStruct:Identifying differentially reactive regions from RNA structurome profiling data

dStruct identifies differentially reactive regions from RNA structurome profiling data. dStruct is compatible with a broad range of structurome profiling technologies, e.g., SHAPE-MaP, DMS-MaPseq, Structure-Seq, SHAPE-Seq, etc. See Choudhary et al., Genome Biology, 2019 for the underlying method.

Maintained by Krishna Choudhary. Last updated 5 months ago.

statisticalmethod structuralprediction sequencing software

16.5 match 2 stars 4.86 score 12 scripts

k3jph

cmna:Computational Methods for Numerical Analysis

Provides the source and examples for James P. Howard, II, "Computational Methods for Numerical Analysis with R," <https://jameshoward.us/cmna/>, a book on numerical methods in R.

Maintained by James Howard. Last updated 4 years ago.

bisection differential-equations heat-equation interpolation least-squares matrix-factorization monte-carlo newton numerical-analysis optimization partial-differential-equations quadrature root-finding secant splines testthat traveling-salesperson wave-equation

14.2 match 16 stars 5.65 score 62 scripts 3 dependents

tidyverse

ellmer:Chat with Large Language Models

Chat with large language models from a range of providers including 'Claude' <https://claude.ai>, 'OpenAI' <https://chatgpt.com>, and more. Supports streaming, asynchronous calls, tool calling, and structured data extraction.

Maintained by Hadley Wickham. Last updated 11 hours ago.

6.3 match 391 stars 12.65 score 98 scripts 7 dependents

bioc

distinct:distinct: a method for differential analyses via hierarchical permutation tests

distinct is a statistical method to perform differential testing between two or more groups of distributions; differential testing is performed via hierarchical non-parametric permutation tests on the cumulative distribution functions (cdfs) of each sample. While most methods for differential expression target differences in the mean abundance between conditions, distinct, by comparing full cdfs, identifies, both, differential patterns involving changes in the mean, as well as more subtle variations that do not involve the mean (e.g., unimodal vs. bi-modal distributions with the same mean). distinct is a general and flexible tool: due to its fully non-parametric nature, which makes no assumptions on how the data was generated, it can be applied to a variety of datasets. It is particularly suitable to perform differential state analyses on single cell data (i.e., differential analyses within sub-populations of cells), such as single cell RNA sequencing (scRNA-seq) and high-dimensional flow or mass cytometry (HDCyto) data. To use distinct one needs data from two or more groups of samples (i.e., experimental conditions), with at least 2 samples (i.e., biological replicates) per group.

Maintained by Simone Tiberi. Last updated 5 months ago.

genetics rnaseq sequencing differentialexpression geneexpression multiplecomparison software transcription statisticalmethod visualization singlecell flowcytometry genetarget openblas cpp

12.5 match 11 stars 6.35 score 34 scripts 1 dependents

btskinner

duawranglr:Securely Wrangle Dataset According to Data Usage Agreement

Create shareable data sets from raw data files that contain protected elements. Relying on master crosswalk files that list restricted variables, package functions warn users about possible violations of data usage agreement and prevent writing protected elements.

Maintained by Benjamin Skinner. Last updated 4 years ago.

data-security data-usage-agreement data-wrangling

14.8 match 9 stars 5.37 score 13 scripts

bioc

Glimma:Interactive visualizations for gene expression analysis

This package produces interactive visualizations for RNA-seq data analysis, utilizing output from limma, edgeR, or DESeq2. It produces interactive htmlwidgets versions of popular RNA-seq analysis plots to enhance the exploration of analysis results by overlaying interactive features. The plots can be viewed in a web browser or embedded in notebook documents.

Maintained by Shian Su. Last updated 1 months ago.

differentialexpression geneexpression microarray reportwriting rnaseq sequencing visualization differential-expression interactive-visualizations

7.5 match 32 stars 10.58 score 600 scripts 1 dependents

damianobaldan

RAC:R Package for Aqua Culture

Solves the individual bioenergetic balance for different aquaculture sea fish (Sea Bream and Sea Bass; Brigolin et al., 2014 <doi:10.3354/aei00093>) and shellfish (Mussel and Clam; Brigolin et al., 2009 <doi:10.1016/j.ecss.2009.01.029>; Solidoro et al., 2000 <doi:10.3354/meps199137>). Allows for spatialized model runs and population simulations.

Maintained by Baldan D.. Last updated 2 years ago.

17.4 match 4.54 score

theeliteanalyst

Riex:IEX Stocks and Market Data

Retrieves efficiently and reliably Investors Exchange ('IEX') stock and market data using 'IEX Cloud API'. The platform is offered by Investors Exchange Group (IEX Group). Main goal is to leverage 'R' capabilities including existing packages to effectively provide financial and statistical analysis as well as visualization in support of fact-based decisions. In addition, continuously improve and enhance 'Riex' by applying best practices and being in tune with users' feedback and requirements. Please, make sure to review and acknowledge Investors Exchange Group (IEX Group) terms and conditions before using 'Riex' (<https://iexcloud.io/terms/>).

Maintained by Myriam Ibrahim. Last updated 4 years ago.

finance financial-analysis financial-data iex iex-api iexcloud

16.8 match 9 stars 4.69 score 11 scripts

mjg211

phaseR:Phase Plane Analysis of One- And Two-Dimensional Autonomous ODE Systems

Performs a qualitative analysis of one- and two-dimensional autonomous ordinary differential equation systems, using phase plane methods. Programs are available to identify and classify equilibrium points, plot the direction field, and plot trajectories for multiple initial conditions. In the one-dimensional case, a program is also available to plot the phase portrait. Whilst in the two-dimensional case, programs are additionally available to plot nullclines and stable/unstable manifolds of saddle points. Many example systems are provided for the user. For further details can be found in Grayling (2014) <doi:10.32614/RJ-2014-023>.

Maintained by Michael J Grayling. Last updated 3 years ago.

biological-modeling differential-equations dynamical-systems ecological-modelling lotka-volterra manifolds modeling-dynamic-systems morris-lecar perturbation-analysis phase-plane sir-model species-interactions van-der-pol

11.8 match 15 stars 6.63 score 94 scripts 1 dependents

bioc

ORFik:Open Reading Frames in Genomics

R package for analysis of transcript and translation features through manipulation of sequence data and NGS data like Ribo-Seq, RNA-Seq, TCP-Seq and CAGE. It is generalized in the sense that any transcript region can be analysed, as the name hints to it was made with investigation of ribosomal patterns over Open Reading Frames (ORFs) as it's primary use case. ORFik is extremely fast through use of C++, data.table and GenomicRanges. Package allows to reassign starts of the transcripts with the use of CAGE-Seq data, automatic shifting of RiboSeq reads, finding of Open Reading Frames for whole genomes and much more.

Maintained by Haakon Tjeldnes. Last updated 27 days ago.

immunooncology software sequencing riboseq rnaseq functionalgenomics coverage alignment dataimport cpp

7.3 match 33 stars 10.63 score 115 scripts 2 dependents

bioc

DifferentialRegulation:Differentially regulated genes from scRNA-seq data

DifferentialRegulation is a method for detecting differentially regulated genes between two groups of samples (e.g., healthy vs. disease, or treated vs. untreated samples), by targeting differences in the balance of spliced and unspliced mRNA abundances, obtained from single-cell RNA-sequencing (scRNA-seq) data. From a mathematical point of view, DifferentialRegulation accounts for the sample-to-sample variability, and embeds multiple samples in a Bayesian hierarchical model. Furthermore, our method also deals with two major sources of mapping uncertainty: i) 'ambiguous' reads, compatible with both spliced and unspliced versions of a gene, and ii) reads mapping to multiple genes. In particular, ambiguous reads are treated separately from spliced and unsplced reads, while reads that are compatible with multiple genes are allocated to the gene of origin. Parameters are inferred via Markov chain Monte Carlo (MCMC) techniques (Metropolis-within-Gibbs).

Maintained by Simone Tiberi. Last updated 5 months ago.

differentialsplicing bayesian genetics rnaseq sequencing differentialexpression geneexpression multiplecomparison software transcription statisticalmethod visualization singlecell genetarget openblas cpp

14.7 match 10 stars 5.30 score 4 scripts

bioc

roar:Identify differential APA usage from RNA-seq alignments

Identify preferential usage of APA sites, comparing two biological conditions, starting from known alternative sites and alignments obtained from standard RNA-seq experiments.

Maintained by Elena Grassi. Last updated 5 months ago.

sequencing highthroughputsequencing rnaseq transcription

15.4 match 4 stars 5.05 score 14 scripts

mbannert

timeseriesdb:A Time Series Database for Official Statistics with R and PostgreSQL

Archive and manage times series data from official statistics. The 'timeseriesdb' package was designed to manage a large catalog of time series from official statistics which are typically published on a monthly, quarterly or yearly basis. Thus timeseriesdb is optimized to handle updates caused by data revision as well as elaborate, multi-lingual meta information.

Maintained by Matthias Bannert. Last updated 6 months ago.

11.3 match 24 stars 6.89 score 26 scripts

bioc

dar:Differential Abundance Analysis by Consensus

Differential abundance testing in microbiome data challenges both parametric and non-parametric statistical methods, due to its sparsity, high variability and compositional nature. Microbiome-specific statistical methods often assume classical distribution models or take into account compositional specifics. These produce results that range within the specificity vs sensitivity space in such a way that type I and type II error that are difficult to ascertain in real microbiome data when a single method is used. Recently, a consensus approach based on multiple differential abundance (DA) methods was recently suggested in order to increase robustness. With dar, you can use dplyr-like pipeable sequences of DA methods and then apply different consensus strategies. In this way we can obtain more reliable results in a fast, consistent and reproducible way.

Maintained by Francesc Catala-Moll. Last updated 5 months ago.

software sequencing microbiome metagenomics multiplecomparison normalization bioconductor biomarker-discovery differential-abundance-analysis feature-selection microbiology phyloseq

13.3 match 2 stars 5.85 score 8 scripts

snoweye

cubfits:Codon Usage Bias Fits

Estimating mutation and selection coefficients on synonymous codon bias usage based on models of ribosome overhead cost (ROC). Multinomial logistic regression and Markov Chain Monte Carlo are used to estimate and predict protein production rates with/without the presence of expressions and measurement errors. Work flows with examples for simulation, estimation and prediction processes are also provided with parallelization speedup. The whole framework is tested with yeast genome and gene expression data of Yassour, et al. (2009) <doi:10.1073/pnas.0812841106>.

Maintained by Wei-Chen Chen. Last updated 3 years ago.

15.9 match 7 stars 4.83 score 32 scripts

rafapereirabr

r5r:Rapid Realistic Routing with 'R5'

Rapid realistic routing on multimodal transport networks (walk, bike, public transport and car) using 'R5', the Rapid Realistic Routing on Real-world and Reimagined networks engine <https://github.com/conveyal/r5>. The package allows users to generate detailed routing analysis or calculate travel time and monetary cost matrices using seamless parallel computing on top of the R5 Java machine. While R5 is developed by Conveyal, the package r5r is independently developed by a team at the Institute for Applied Economic Research (Ipea) with contributions from collaborators. Apart from the documentation in this package, users will find additional information on R5 documentation at <https://docs.conveyal.com/>. Although we try to keep new releases of r5r in synchrony with R5, the development of R5 follows Conveyal's independent update process. Hence, users should confirm the R5 version implied by the Conveyal user manual (see <https://docs.conveyal.com/changelog>) corresponds with the R5 version that r5r depends on. This version of r5r depends on R5 v7.1.

Maintained by Rafael H. M. Pereira. Last updated 7 days ago.

openjdk

13.5 match 5.62 score 432 scripts

yihui

formatR:Format R Code Automatically

Provides a function tidy_source() to format R source code. Spaces and indent will be added to the code automatically, and comments will be preserved under certain conditions, so that R code will be more human-readable and tidy. There is also a Shiny app as a user interface in this package (see tidy_app()).

Maintained by Yihui Xie. Last updated 1 years ago.

code-formatter

5.0 match 259 stars 15.07 score 1.4k scripts 1.2k dependents

bioc

scMET:Bayesian modelling of cell-to-cell DNA methylation heterogeneity

High-throughput single-cell measurements of DNA methylomes can quantify methylation heterogeneity and uncover its role in gene regulation. However, technical limitations and sparse coverage can preclude this task. scMET is a hierarchical Bayesian model which overcomes sparsity, sharing information across cells and genomic features to robustly quantify genuine biological heterogeneity. scMET can identify highly variable features that drive epigenetic heterogeneity, and perform differential methylation and variability analyses. We illustrate how scMET facilitates the characterization of epigenetically distinct cell populations and how it enables the formulation of novel hypotheses on the epigenetic regulation of gene expression.

Maintained by Andreas C. Kapourani. Last updated 5 months ago.

immunooncology dnamethylation differentialmethylation differentialexpression geneexpression generegulation epigenetics genetics clustering featureextraction regression bayesian sequencing coverage singlecell bayesian-inference generalised-linear-models heterogeneity hierarchical-models methylation-analysis single-cell cpp

11.9 match 20 stars 6.23 score 42 scripts

rstudio

renv:Project Environments

A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.

Maintained by Kevin Ushey. Last updated 3 days ago.

4.0 match 1.0k stars 18.55 score 1.5k scripts 113 dependents

bioc

methylInheritance:Permutation-Based Analysis associating Conserved Differentially Methylated Elements Across Multiple Generations to a Treatment Effect

Permutation analysis, based on Monte Carlo sampling, for testing the hypothesis that the number of conserved differentially methylated elements, between several generations, is associated to an effect inherited from a treatment and that stochastic effect can be dismissed.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion epigenetics dnamethylation differentialmethylation methylseq software immunooncology statisticalmethod wholegenome sequencing analysis bioconductor bioinformatics cpg differentially-methylated-elements inheritance monte-carlo-sampling permutation

16.0 match 4.60 score 1 scripts

bioc

sccomp:Tests differences in cell-type proportion for single-cell data, robust to outliers

A robust and outlier-aware method for testing differences in cell-type proportion in single-cell data. This model can infer changes in tissue composition and heterogeneity, and can produce realistic data simulations based on any existing dataset. This model can also transfer knowledge from a large set of integrated datasets to increase accuracy further.

Maintained by Stefano Mangiola. Last updated 16 days ago.

bayesian regression differentialexpression singlecell batch-correction composition cytof differential-proportion microbiome multilevel proportions random-effects single-cell unwanted-variation

8.8 match 99 stars 8.41 score 69 scripts

bioc

Maaslin2:"Multivariable Association Discovery in Population-scale Meta-omics Studies"

MaAsLin2 is comprehensive R package for efficiently determining multivariable association between clinical metadata and microbial meta'omic features. MaAsLin2 relies on general linear models to accommodate most modern epidemiological study designs, including cross-sectional and longitudinal, and offers a variety of data exploration, normalization, and transformation methods. MaAsLin2 is the next generation of MaAsLin.

Maintained by Lauren McIver. Last updated 5 months ago.

metagenomics software microbiome normalization biobakery bioconductor differential-abundance-analysis false-discovery-rate multiple-covariates public repeated-measures tools

6.7 match 133 stars 11.03 score 532 scripts 3 dependents

bioc

MIRit:Integrate microRNA and gene expression to decipher pathway complexity

MIRit is an R package that provides several methods for investigating the relationships between miRNAs and genes in different biological conditions. In particular, MIRit allows to explore the functions of dysregulated miRNAs, and makes it possible to identify miRNA-gene regulatory axes that control biological pathways, thus enabling the users to unveil the complexity of miRNA biology. MIRit is an all-in-one framework that aims to help researchers in all the central aspects of an integrative miRNA-mRNA analyses, from differential expression analysis to network characterization.

Maintained by Jacopo Ronchi. Last updated 2 days ago.

software generegulation networkenrichment networkinference epigenetics functionalgenomics systemsbiology network pathways geneexpression differentialexpression mirna mirna-mrna-interaction mirna-seq mirnaseq-analysis cpp

18.3 match 4.00 score 2 scripts

bioc

netZooR:Unified methods for the inference and analysis of gene regulatory networks

netZooR unifies the implementations of several Network Zoo methods (netzoo, netzoo.github.io) into a single package by creating interfaces between network inference and network analysis methods. Currently, the package has 3 methods for network inference including PANDA and its optimized implementation OTTER (network reconstruction using mutliple lines of biological evidence), LIONESS (single-sample network inference), and EGRET (genotype-specific networks). Network analysis methods include CONDOR (community detection), ALPACA (differential community detection), CRANE (significance estimation of differential modules), MONSTER (estimation of network transition states). In addition, YARN allows to process gene expresssion data for tissue-specific analyses and SAMBAR infers missing mutation data based on pathway information.

Maintained by Tara Eicher. Last updated 9 days ago.

networkinference network generegulation geneexpression transcription microarray graphandnetwork gene-regulatory-network transcription-factors

9.2 match 105 stars 7.98 score

bioc

extraChIPs:Additional functions for working with ChIP-Seq data

This package builds on existing tools and adds some simple but extremely useful capabilities for working wth ChIP-Seq data. The focus is on detecting differential binding windows/regions. One set of functions focusses on set-operations retaining mcols for GRanges objects, whilst another group of functions are to aid visualisation of results. Coercion to tibble objects is also implemented.

Maintained by Stevie Pederson. Last updated 15 days ago.

chipseq hic sequencing coverage

10.8 match 7 stars 6.67 score 25 scripts

hugheylab

limorhyde2:Quantify Rhythmicity and Differential Rhythmicity in Genomic Data

Fit linear models based on periodic splines, moderate model coefficients using multivariate adaptive shrinkage, then compute properties of the moderated curves.

Maintained by Jake Hughey. Last updated 1 years ago.

15.1 match 4.78 score 2 scripts

bioc

edge:Extraction of Differential Gene Expression

The edge package implements methods for carrying out differential expression analyses of genome-wide gene expression studies. Significance testing using the optimal discovery procedure and generalized likelihood ratio tests (equivalent to F-tests and t-tests) are implemented for general study designs. Special functions are available to facilitate the analysis of common study designs, including time course experiments. Other packages such as sva and qvalue are integrated in edge to provide a wide range of tools for gene expression analysis.

Maintained by John D. Storey. Last updated 5 months ago.

multiplecomparison differentialexpression timecourse regression geneexpression dataimport

9.2 match 21 stars 7.77 score 62 scripts

tomkellygenetics

leiden:R Implementation of Leiden Clustering Algorithm

Implements the 'Python leidenalg' module to be called in R. Enables clustering using the leiden algorithm for partition a graph into communities. See the 'Python' repository for more details: <https://github.com/vtraag/leidenalg> Traag et al (2018) From Louvain to Leiden: guaranteeing well-connected communities. <arXiv:1810.08473>.

Maintained by S. Thomas Kelly. Last updated 10 months ago.

8.0 match 38 stars 8.90 score 180 scripts 3 dependents

bioc

RolDE:RolDE: Robust longitudinal Differential Expression

RolDE detects longitudinal differential expression between two conditions in noisy high-troughput data. Suitable even for data with a moderate amount of missing values.RolDE is a composite method, consisting of three independent modules with different approaches to detecting longitudinal differential expression. The combination of these diverse modules allows RolDE to robustly detect varying differences in longitudinal trends and expression levels in diverse data types and experimental settings.

Maintained by Medical Bioinformatics Centre. Last updated 5 months ago.

statisticalmethod software timecourse regression proteomics differentialexpression

13.7 match 5 stars 5.18 score 1 scripts

cgoo4

usedthese:Summarises Package & Function Usage

Consistent with 'knitr' syntax highlighting, 'usedthese' adds a summary table of package & function usage to a Quarto document and enables aggregation of usage across a website.

Maintained by Carl Goodwin. Last updated 8 months ago.

quarto

10.6 match 7 stars 6.70 score 120 scripts

shosaco

vistime:Pretty Timelines in R

A library for creating time based charts, like Gantt or timelines. Possible outputs include 'ggplot2' diagrams, 'plotly.js' graphs, 'Highcharts.js' widgets and data.frames. Results can be used in the 'RStudio' viewer pane, in 'RMarkdown' documents or in Shiny apps. In the interactive outputs created by vistime() and hc_vistime(), you can interact with the plot using mouse hover or zoom.

Maintained by Sandro Raabe. Last updated 6 months ago.

charts timelines

7.5 match 174 stars 9.37 score 142 scripts 1 dependents

r-lum

RLumModel:Solving Ordinary Differential Equations to Understand Luminescence

A collection of functions to simulate luminescence signals in quartz and Al2O3 based on published models.

Maintained by Johannes Friedrich. Last updated 3 years ago.

differential-equations energy-band-model geochronology luminescence luminescence-models modelling quartz simulation openblas cpp

12.2 match 5 stars 5.73 score 18 scripts 1 dependents

r-dbi

DBI:R Database Interface

A database interface definition for communication between R and relational database management systems. All classes in this package are virtual and need to be extended by the various R/DBMS implementations.

Maintained by Kirill Müller. Last updated 3 months ago.

database interface

3.3 match 302 stars 20.88 score 19k scripts 2.9k dependents

bioc

scde:Single Cell Differential Expression

The scde package implements a set of statistical methods for analyzing single-cell RNA-seq data. scde fits individual error models for single-cell RNA-seq measurements. These models can then be used for assessment of differential expression between groups of cells, as well as other types of analysis. The scde package also contains the pagoda framework which applies pathway and gene set overdispersion analysis to identify and characterize putative cell subpopulations based on transcriptional signatures. The overall approach to the differential expression analysis is detailed in the following publication: "Bayesian approach to single-cell differential expression analysis" (Kharchenko PV, Silberstein L, Scadden DT, Nature Methods, doi: 10.1038/nmeth.2967). The overall approach to subpopulation identification and characterization is detailed in the following pre-print: "Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis" (Fan J, Salathia N, Liu R, Kaeser G, Yung Y, Herman J, Kaper F, Fan JB, Zhang K, Chun J, and Kharchenko PV, Nature Methods, doi:10.1038/nmeth.3734).

Maintained by Evan Biederstedt. Last updated 5 months ago.

immunooncology rnaseq statisticalmethod differentialexpression bayesian transcription software analysis bioinformatics heterogenity ngs single-cell transcriptomics openblas cpp openmp

9.2 match 173 stars 7.53 score 141 scripts

dgrun

RaceID:Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Application of 'RaceID' allows inference of cell types and prediction of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) <DOI:10.1038/nmeth.4662>). 'VarID2' is part of this package and allows quantification of biological gene expression noise at single-cell resolution (Rosales-Alvarez, R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, D. (2023) <DOI:10.1186/s13059-023-02974-1>).

Maintained by Dominic Grün. Last updated 4 months ago.

cpp

14.6 match 4.74 score 110 scripts

dcourvoisier

doremi:Dynamics of Return to Equilibrium During Multiple Inputs

Provides models to fit the dynamics of a regulated system experiencing exogenous inputs. The underlying models use differential equations and linear mixed-effects regressions to estimate the coefficients of the equation. With them, the functions can provide an estimated signal. The package provides simulation and analysis functions and also print, summary, plot and predict methods, adapted to the function outputs, for easy implementation and presentation of results.

Maintained by Mongin Denis. Last updated 3 years ago.

15.5 match 4.48 score 25 scripts 1 dependents

kharchenkolab

pagoda2:Single Cell Analysis and Differential Expression

Analyzing and interactively exploring large-scale single-cell RNA-seq datasets. 'pagoda2' primarily performs normalization and differential gene expression analysis, with an interactive application for exploring single-cell RNA-seq datasets. It performs basic tasks such as cell size normalization, gene variance normalization, and can be used to identify subpopulations and run differential expression within individual samples. 'pagoda2' was written to rapidly process modern large-scale scRNAseq datasets of approximately 1e6 cells. The companion web application allows users to explore which gene expression patterns form the different subpopulations within your data. The package also serves as the primary method for preprocessing data for conos, <https://github.com/kharchenkolab/conos>. This package interacts with data available through the 'p2data' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/pagoda2>. The size of the 'p2data' package is approximately 6 MB.

Maintained by Evan Biederstedt. Last updated 1 years ago.

scrna-seq single-cell single-cell-rna-seq transcriptomics openblas cpp openmp

8.6 match 222 stars 8.00 score 282 scripts

bioc

enrichViewNet:From functional enrichment results to biological networks

This package enables the visualization of functional enrichment results as network graphs. First the package enables the visualization of enrichment results, in a format corresponding to the one generated by gprofiler2, as a customizable Cytoscape network. In those networks, both gene datasets (GO terms/pathways/protein complexes) and genes associated to the datasets are represented as nodes. While the edges connect each gene to its dataset(s). The package also provides the option to create enrichment maps from functional enrichment results. Enrichment maps enable the visualization of enriched terms into a network with edges connecting overlapping genes.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion software network networkenrichment go cystocape functional-enrichment

12.3 match 5 stars 5.54 score 6 scripts

bioc

DEsingle:DEsingle for detecting three types of differential expression in single-cell RNA-seq data

DEsingle is an R package for differential expression (DE) analysis of single-cell RNA-seq (scRNA-seq) data. It defines and detects 3 types of differentially expressed genes between two groups of single cells, with regard to different expression status (DEs), differential expression abundance (DEa), and general differential expression (DEg). DEsingle employs Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect the 3 types of DE genes. Results showed that DEsingle outperforms existing methods for scRNA-seq DE analysis, and can reveal different types of DE genes that are enriched in different biological functions.

Maintained by Zhun Miao. Last updated 5 months ago.

differentialexpression geneexpression singlecell immunooncology rnaseq transcriptomics sequencing preprocessing software

9.2 match 31 stars 7.42 score 28 scripts

bioc

bambu:Context-Aware Transcript Quantification from Long Read RNA-Seq data

bambu is a R package for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis such as differential gene expression or transcript usage.

Maintained by Ying Chen. Last updated 1 months ago.

alignment coverage differentialexpression featureextraction geneexpression genomeannotation genomeassembly immunooncology longread multiplecomparison normalization rnaseq regression sequencing software transcription transcriptomics bambu bioconductor long-reads nanopore nanopore-sequencing rna-seq rna-seq-analysis transcript-quantification transcript-reconstruction cpp

7.5 match 197 stars 9.03 score 91 scripts 1 dependents

adeverse

ade4:Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

Tools for multivariate data analysis. Several methods are provided for the analysis (i.e., ordination) of one-table (e.g., principal component analysis, correspondence analysis), two-table (e.g., coinertia analysis, redundancy analysis), three-table (e.g., RLQ analysis) and K-table (e.g., STATIS, multiple coinertia analysis). The philosophy of the package is described in Dray and Dufour (2007) <doi:10.18637/jss.v022.i04>.

Maintained by Aurélie Siberchicot. Last updated 12 days ago.

openblas cpp

4.5 match 39 stars 14.96 score 2.2k scripts 256 dependents

bioc

iSEEde:iSEE extension for panels related to differential expression analysis

This package contains diverse functionality to extend the usage of the iSEE package, including additional classes for the panels or modes facilitating the analysis of differential expression results. This package does not perform differential expression. Instead, it provides methods to embed precomputed differential expression results in a SummarizedExperiment object, in a manner that is compatible with interactive visualisation in iSEE applications.

Maintained by Kevin Rue-Albrecht. Last updated 4 months ago.

software infrastructure differentialexpression bioconductor hacktoberfest iseeu

12.3 match 1 stars 5.38 score 15 scripts

bioc

RiboDiPA:Differential pattern analysis for Ribo-seq data

This package performs differential pattern analysis for Ribo-seq data. It identifies genes with significantly different patterns in the ribosome footprint between two conditions. RiboDiPA contains five major components including bam file processing, P-site mapping, data binning, differential pattern analysis and footprint visualization.

Maintained by Ji-Ping Wang. Last updated 3 months ago.

riboseq geneexpression generegulation differentialexpression sequencing coverage alignment rnaseq immunooncology qualitycontrol dataimport software normalization cpp

15.4 match 4.30 score 1 scripts

bioc

derfinder:Annotation-agnostic differential expression analysis of RNA-seq data at base-pair resolution via the DER Finder approach

This package provides functions for annotation-agnostic differential expression analysis of RNA-seq data. Two implementations of the DER Finder approach are included in this package: (1) single base-level F-statistics and (2) DER identification at the expressed regions-level. The DER Finder approach can also be used to identify differentially bounded ChIP-seq peaks.

Maintained by Leonardo Collado-Torres. Last updated 3 months ago.

differentialexpression sequencing rnaseq chipseq differentialpeakcalling software immunooncology coverage annotation-agnostic bioconductor derfinder

6.5 match 42 stars 10.03 score 78 scripts 6 dependents

bioc

variancePartition:Quantify and interpret drivers of variation in multilevel gene expression experiments

Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.

Maintained by Gabriel E. Hoffman. Last updated 2 months ago.

rnaseq geneexpression genesetenrichment differentialexpression batcheffect qualitycontrol regression epigenetics functionalgenomics transcriptomics normalization preprocessing microarray immunooncology software

5.6 match 7 stars 11.69 score 1.1k scripts 3 dependents

eonurk

cinaR:A Computational Pipeline for Bulk 'ATAC-Seq' Profiles

Differential analyses and Enrichment pipeline for bulk 'ATAC-seq' data analyses. This package combines different packages to have an ultimate package for both data analyses and visualization of 'ATAC-seq' data. Methods are described in 'Karakaslar et al.' (2021) <doi:10.1101/2021.03.05.434143>.

Maintained by Onur Karakaslar. Last updated 10 months ago.

atac-seq differential-analysis enrichment-analysis gene-sets

11.8 match 13 stars 5.52 score 51 scripts

paulojus

geoR:Analysis of Geostatistical Data

Geostatistical analysis including variogram-based, likelihood-based and Bayesian methods. Software companion for Diggle and Ribeiro (2007) <doi:10.1007/978-0-387-48536-2>.

Maintained by Paulo Justiniano Ribeiro Jr. Last updated 1 years ago.

8.6 match 10 stars 7.57 score 1.8k scripts 12 dependents

luca-scr

GA:Genetic Algorithms

Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach. For more details see Scrucca (2013) <doi:10.18637/jss.v053.i04> and Scrucca (2017) <doi:10.32614/RJ-2017-008>.

Maintained by Luca Scrucca. Last updated 6 months ago.

genetic-algorithm optimisation cpp

5.6 match 93 stars 11.58 score 624 scripts 52 dependents

desctable

desctable:Produce Descriptive and Comparative Tables Easily

Easily create descriptive and comparative tables. It makes use and integrates directly with the tidyverse family of packages, and pipes. Tables are produced as (nested) dataframes for easy manipulation.

Maintained by Maxime Wack. Last updated 3 years ago.

markdown statistics tidyverse

9.5 match 52 stars 6.85 score 45 scripts

bioc

BioCor:Functional similarities

Calculates functional similarities based on the pathways described on KEGG and REACTOME or in gene sets. These similarities can be calculated for pathways or gene sets, genes, or clusters and combined with other similarities. They can be used to improve networks, gene selection, testing relationships...

Maintained by Lluís Revilla Sancho. Last updated 5 months ago.

statisticalmethod clustering geneexpression network pathways networkenrichment systemsbiology bioconductor-packages bioinformatics functional-similarity gene gene-sets pathway-analysis similarity similarity-measurement

9.8 match 14 stars 6.59 score

bioc

NoRCE:NoRCE: Noncoding RNA Sets Cis Annotation and Enrichment

While some non-coding RNAs (ncRNAs) are assigned critical regulatory roles, most remain functionally uncharacterized. This presents a challenge whenever an interesting set of ncRNAs needs to be analyzed in a functional context. Transcripts located close-by on the genome are often regulated together. This genomic proximity on the sequence can hint to a functional association. We present a tool, NoRCE, that performs cis enrichment analysis for a given set of ncRNAs. Enrichment is carried out using the functional annotations of the coding genes located proximal to the input ncRNAs. Other biologically relevant information such as topologically associating domain (TAD) boundaries, co-expression patterns, and miRNA target prediction information can be incorporated to conduct a richer enrichment analysis. To this end, NoRCE includes several relevant datasets as part of its data repository, including cell-line specific TAD boundaries, functional gene sets, and expression data for coding & ncRNAs specific to cancer. Additionally, the users can utilize custom data files in their investigation. Enrichment results can be retrieved in a tabular format or visualized in several different ways. NoRCE is currently available for the following species: human, mouse, rat, zebrafish, fruit fly, worm, and yeast.

Maintained by Gulden Olgun. Last updated 5 months ago.

biologicalquestion differentialexpression genomeannotation genesetenrichment genetarget genomeassembly go

14.0 match 1 stars 4.60 score 6 scripts

bioc

gatom:Finding an Active Metabolic Module in Atom Transition Network

This package implements a metabolic network analysis pipeline to identify an active metabolic module based on high throughput data. The pipeline takes as input transcriptional and/or metabolic data and finds a metabolic subnetwork (module) most regulated between the two conditions of interest. The package further provides functions for module post-processing, annotation and visualization.

Maintained by Alexey Sergushichev. Last updated 5 months ago.

geneexpression differentialexpression pathways network

12.1 match 6 stars 5.26 score 8 scripts

bioc

BANDITS:BANDITS: Bayesian ANalysis of DIfferenTial Splicing

BANDITS is a Bayesian hierarchical model for detecting differential splicing of genes and transcripts, via differential transcript usage (DTU), between two or more conditions. The method uses a Bayesian hierarchical framework, which allows for sample specific proportions in a Dirichlet-Multinomial model, and samples the allocation of fragments to the transcripts. Parameters are inferred via Markov chain Monte Carlo (MCMC) techniques and a DTU test is performed via a multivariate Wald test on the posterior densities for the average relative abundance of transcripts.

Maintained by Simone Tiberi. Last updated 5 months ago.

differentialsplicing alternativesplicing bayesian genetics rnaseq sequencing differentialexpression geneexpression multiplecomparison software transcription statisticalmethod visualization openblas cpp

11.1 match 17 stars 5.75 score 11 scripts 1 dependents

bioc

treeclimbR:An algorithm to find optimal signal levels in a tree

The arrangement of hypotheses in a hierarchical structure appears in many research fields and often indicates different resolutions at which data can be viewed. This raises the question of which resolution level the signal should best be interpreted on. treeclimbR provides a flexible method to select optimal resolution levels (potentially different levels in different parts of the tree), rather than cutting the tree at an arbitrary level. treeclimbR uses a tuning parameter to generate candidate resolutions and from these selects the optimal one.

Maintained by Charlotte Soneson. Last updated 3 months ago.

statisticalmethod cellbasedassays

9.1 match 20 stars 7.00 score 45 scripts

tushiqi

MAnorm2:Tools for Normalizing and Comparing ChIP-seq Samples

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the premier technology for profiling genome-wide localization of chromatin-binding proteins, including transcription factors and histones with various modifications. This package provides a robust method for normalizing ChIP-seq signals across individual samples or groups of samples. It also designs a self-contained system of statistical models for calling differential ChIP-seq signals between two or more biological conditions as well as for calling hypervariable ChIP-seq signals across samples. Refer to Tu et al. (2021) <doi:10.1101/gr.262675.120> and Chen et al. (2022) <doi:10.1186/s13059-022-02627-9> for associated statistical details.

Maintained by Shiqi Tu. Last updated 2 years ago.

chip-seq differential-analysis empirical-bayes winsorize-values

11.5 match 32 stars 5.48 score 19 scripts

geco-bern

rsofun:The P-Model and BiomeE Modelling Framework

Implements the Simulating Optimal FUNctioning framework for site-scale simulations of ecosystem processes, including model calibration. It contains 'Fortran 90' modules for the P-model (Stocker et al. (2020) <doi:10.5194/gmd-13-1545-2020>), SPLASH (Davis et al. (2017) <doi:10.5194/gmd-10-689-2017>) and BiomeE (Weng et al. (2015) <doi:10.5194/bg-12-2655-2015>).

Maintained by Benjamin Stocker. Last updated 13 days ago.

dgvm growth modeling p-model simulation vegetation-dynamics fortran

7.1 match 26 stars 8.77 score 119 scripts

bioc

tadar:Transcriptome Analysis of Differential Allelic Representation

This package provides functions to standardise the analysis of Differential Allelic Representation (DAR). DAR compromises the integrity of Differential Expression analysis results as it can bias expression, influencing the classification of genes (or transcripts) as being differentially expressed. DAR analysis results in an easy-to-interpret value between 0 and 1 for each genetic feature of interest, where 0 represents identical allelic representation and 1 represents complete diversity. This metric can be used to identify features prone to false-positive calls in Differential Expression analysis, and can be leveraged with statistical methods to alleviate the impact of such artefacts on RNA-seq data.

Maintained by Lachlan Baer. Last updated 2 months ago.

sequencing rnaseq snp genomicvariation variantannotation differentialexpression

12.5 match 1 stars 4.95 score 4 scripts

afukushima

DiffCorr:Analyzing and Visualizing Differential Correlation Networks in Biological Data

A method for identifying pattern changes between 2 experimental conditions in correlation networks (e.g., gene co-expression networks), which builds on a commonly used association measure, such as Pearson's correlation coefficient. This package includes functions to calculate correlation matrices for high-dimensional dataset and to test differential correlation, which means the changes in the correlation relationship among variables (e.g., genes and metabolites) between 2 experimental conditions.

Maintained by Atsushi Fukushima. Last updated 6 months ago.

9.1 match 5 stars 6.81 score 29 scripts 1 dependents

bioc

hermes:Preprocessing, analyzing, and reporting of RNA-seq data

Provides classes and functions for quality control, filtering, normalization and differential expression analysis of pre-processed `RNA-seq` data. Data can be imported from `SummarizedExperiment` as well as `matrix` objects and can be annotated from `BioMart`. Filtering for genes without too low expression or containing required annotations, as well as filtering for samples with sufficient correlation to other samples or total number of reads is supported. The standard normalization methods including cpm, rpkm and tpm can be used, and 'DESeq2` as well as voom differential expression analyses are available.

Maintained by Daniel Sabanés Bové. Last updated 5 months ago.

rnaseq differentialexpression normalization preprocessing qualitycontrol rna-seq statistical-engineering

8.0 match 11 stars 7.77 score 48 scripts 1 dependents

datalorax

equatiomatic:Transform Models into 'LaTeX' Equations

The goal of 'equatiomatic' is to reduce the pain associated with writing 'LaTeX' formulas from fitted models. The primary function of the package, extract_eq(), takes a fitted model object as its input and returns the corresponding 'LaTeX' code for the model.

Maintained by Philippe Grosjean. Last updated 7 days ago.

5.3 match 619 stars 11.75 score 424 scripts 5 dependents

bioc

proDA:Differential Abundance Analysis of Label-Free Mass Spectrometry Data

Account for missing values in label-free mass spectrometry data without imputation. The package implements a probabilistic dropout model that ensures that the information from observed and missing values are properly combined. It adds empirical Bayesian priors to increase power to detect differentially abundant proteins.

Maintained by Constantin Ahlmann-Eltze. Last updated 5 months ago.

proteomics massspectrometry differentialexpression bayesian regression software normalization qualitycontrol

8.2 match 18 stars 7.49 score 48 scripts 1 dependents

glmmtmb

glmmTMB:Generalized Linear Mixed Models using Template Model Builder

Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.

Maintained by Mollie Brooks. Last updated 11 days ago.

cpp openmp

3.6 match 312 stars 16.77 score 3.7k scripts 24 dependents

myles-lewis

glmmSeq:General Linear Mixed Models for Gene-Level Differential Expression

Using mixed effects models to analyse longitudinal gene expression can highlight differences between sample groups over time. The most widely used differential gene expression tools are unable to fit linear mixed effect models, and are less optimal for analysing longitudinal data. This package provides negative binomial and Gaussian mixed effects models to fit gene expression and other biological data across repeated samples. This is particularly useful for investigating changes in RNA-Sequencing gene expression between groups of individuals over time, as described in: Rivellese, F., Surace, A. E., Goldmann, K., Sciacca, E., Cubuk, C., Giorli, G., ... Lewis, M. J., & Pitzalis, C. (2022) Nature medicine <doi:10.1038/s41591-022-01789-0>.

Maintained by Myles Lewis. Last updated 2 months ago.

bioinformatics differential-gene-expression gene-expression glmm mixed-models transcriptomics

10.0 match 19 stars 6.11 score 45 scripts

rikenbit

dcTensor:Discrete Matrix/Tensor Decomposition

Semi-Binary and Semi-Ternary Matrix Decomposition are performed based on Non-negative Matrix Factorization (NMF) and Singular Value Decomposition (SVD). For the details of the methods, see the reference section of GitHub README.md <https://github.com/rikenbit/dcTensor>.

Maintained by Koki Tsuyuzaki. Last updated 10 months ago.

12.0 match 3 stars 5.08 score

bioc

annotate:Annotation for microarrays

Using R enviroments for annotation.

Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.

annotation pathways go

5.3 match 11.41 score 812 scripts 243 dependents

r-forge

distrMod:Object Oriented Implementation of Probability Models

Implements S4 classes for probability models based on packages 'distr' and 'distrEx'.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

9.1 match 6.71 score 139 scripts 6 dependents

bioc

MAST:Model-based Analysis of Single Cell Transcriptomics

Methods and models for handling zero-inflated single cell assay data.

Maintained by Andrew McDavid. Last updated 5 months ago.

geneexpression differentialexpression genesetenrichment rnaseq transcriptomics singlecell

4.8 match 230 stars 12.75 score 1.8k scripts 5 dependents

bioc

Spectra:Spectra Infrastructure for Mass Spectrometry Data

The Spectra package defines an efficient infrastructure for storing and handling mass spectrometry spectra and functionality to subset, process, visualize and compare spectra data. It provides different implementations (backends) to store mass spectrometry data. These comprise backends tuned for fast data access and processing and backends for very large data sets ensuring a small memory footprint.

Maintained by RforMassSpectrometry Package Maintainer. Last updated 9 days ago.

infrastructure proteomics massspectrometry metabolomics bioconductor hacktoberfest mass-spectrometry

4.6 match 41 stars 13.01 score 254 scripts 35 dependents

kassambara

ggpubr:'ggplot2' Based Publication Ready Plots

The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.

Maintained by Alboukadel Kassambara. Last updated 2 years ago.

3.6 match 1.2k stars 16.68 score 65k scripts 409 dependents

caranathunge

promor:Proteomics Data Analysis and Modeling Tools

A comprehensive, user-friendly package for label-free proteomics data analysis and machine learning-based modeling. Data generated from 'MaxQuant' can be easily used to conduct differential expression analysis, build predictive models with top protein candidates, and assess model performance. promor includes a suite of tools for quality control, visualization, missing data imputation (Lazar et. al. (2016) <doi:10.1021/acs.jproteome.5b00981>), differential expression analysis (Ritchie et. al. (2015) <doi:10.1093/nar/gkv007>), and machine learning-based modeling (Kuhn (2008) <doi:10.18637/jss.v028.i05>).

Maintained by Chathurani Ranathunge. Last updated 2 years ago.

biomarkers differential-expression lfq machine-learning mass-spectrometry modeling proteomics

11.9 match 15 stars 5.02 score 14 scripts

bioc

iCOBRA:Comparison and Visualization of Ranking and Assignment Methods

This package provides functions for calculation and visualization of performance metrics for evaluation of ranking and binary classification (assignment) methods. Various types of performance plots can be generated programmatically. The package also contains a shiny application for interactive exploration of results.

Maintained by Charlotte Soneson. Last updated 3 months ago.

classification visualization

6.8 match 14 stars 8.86 score 192 scripts 1 dependents

satijalab

Seurat:Tools for Single Cell Genomics

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.

Maintained by Paul Hoffman. Last updated 1 years ago.

human-cell-atlas single-cell-genomics single-cell-rna-seq cpp

3.5 match 2.4k stars 16.86 score 50k scripts 73 dependents

rstudio

rsconnect:Deploy Docs, Apps, and APIs to 'Posit Connect', 'shinyapps.io', and 'RPubs'

Programmatic deployment interface for 'RPubs', 'shinyapps.io', and 'Posit Connect'. Supported content types include R Markdown documents, Shiny applications, Plumber APIs, plots, and static web content.

Maintained by Aron Atkins. Last updated 15 days ago.

4.0 match 139 stars 14.90 score 3.1k scripts 6 dependents

bioc

benchdamic:Benchmark of differential abundance methods on microbiome data

Starting from a microbiome dataset (16S or WMS with absolute count values) it is possible to perform several analysis to assess the performances of many differential abundance detection methods. A basic and standardized version of the main differential abundance analysis methods is supplied but the user can also add his method to the benchmark. The analyses focus on 4 main aspects: i) the goodness of fit of each method's distributional assumptions on the observed count data, ii) the ability to control the false discovery rate, iii) the within and between method concordances, iv) the truthfulness of the findings if any apriori knowledge is given. Several graphical functions are available for result visualization.

Maintained by Matteo Calgaro. Last updated 4 months ago.

metagenomics microbiome differentialexpression multiplecomparison normalization preprocessing software benchmark differential-abundance-methods

10.4 match 6 stars 5.73 score 8 scripts

bioc

NOISeq:Exploratory analysis and differential expression for RNA-seq data

Analysis of RNA-seq expression data or other similar kind of data. Exploratory plots to evualuate saturation, count distribution, expression per chromosome, type of detected features, features length, etc. Differential expression between two experimental conditions with no parametric assumptions.

Maintained by Sonia Tarazona. Last updated 5 months ago.

immunooncology rnaseq differentialexpression visualization sequencing

8.8 match 6.70 score 207 scripts 4 dependents

cran

Platypus:Single-Cell Immune Repertoire and Gene Expression Analysis

We present 'Platypus', an open-source software platform providing a user-friendly interface to investigate B-cell receptor and T-cell receptor repertoires from scSeq experiments. 'Platypus' provides a framework to automate and ease the analysis of single-cell immune repertoires while also incorporating transcriptional information involving unsupervised clustering, gene expression and gene ontology. This R version of 'Platypus' is part of the 'ePlatypus' ecosystem for computational analysis of immunogenomics data: Yermanos et al. (2021) <doi:10.1093/nargab/lqab023>, Cotet et al. (2023) <doi:10.1093/bioinformatics/btad553>.

Maintained by Alexander Yermanos. Last updated 5 months ago.

12.8 match 4.58 score 38 scripts

florianhartig

BayesianTools:General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

General-purpose MCMC and SMC samplers, as well as plots and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.

Maintained by Florian Hartig. Last updated 1 years ago.

bayes ecological-models mcmc optimization smc systems-biology cpp

5.7 match 122 stars 10.17 score 580 scripts 5 dependents

bioc

ABSSeq:ABSSeq: a new RNA-Seq analysis method based on modelling absolute expression differences

Inferring differential expression genes by absolute counts difference between two groups, utilizing Negative binomial distribution and moderating fold-change according to heterogeneity of dispersion across expression level.

Maintained by Wentao Yang. Last updated 5 months ago.

differentialexpression

12.5 match 4.62 score 1 scripts 1 dependents

hms-dbmi

UpSetR:A More Scalable Alternative to Venn and Euler Diagrams for Visualizing Intersecting Sets

Creates visualizations of intersecting sets using a novel matrix design, along with visualizations of several common set, element and attribute related tasks (Conway 2017) <doi:10.1093/bioinformatics/btx364>.

Maintained by Jake Conway. Last updated 4 years ago.

gehlenborglab ggplot2 upset upsetr visualization

3.8 match 781 stars 15.33 score 4.8k scripts 42 dependents

bioc

maSigPro:Significant Gene Expression Profile Differences in Time Course Gene Expression Data

maSigPro is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray and RNA-Seq experiments.

Maintained by Maria Jose Nueda. Last updated 5 months ago.

microarray rna-seq differential expression timecourse

10.9 match 5.18 score 76 scripts

cb4ds

periscope:Enterprise Streamlined 'Shiny' Application Framework

An enterprise-targeted scalable and UI-standardized 'shiny' framework including a variety of developer convenience functions with the goal of both streamlining robust application development while assisting with creating a consistent user experience regardless of application or developer.

Maintained by Constance Brett. Last updated 2 months ago.

8.0 match 18 stars 7.02 score 73 scripts

bioc

scp:Mass Spectrometry-Based Single-Cell Proteomics Data Analysis

Utility functions for manipulating, processing, and analyzing mass spectrometry-based single-cell proteomics data. The package is an extension to the 'QFeatures' package and relies on 'SingleCellExpirement' to enable single-cell proteomics analyses. The package offers the user the functionality to process quantitative table (as generated by MaxQuant, Proteome Discoverer, and more) into data tables ready for downstream analysis and data visualization.

Maintained by Christophe Vanderaa. Last updated 16 days ago.

geneexpression proteomics singlecell massspectrometry preprocessing cellbasedassays bioconductor mass-spectrometry single-cell software

6.3 match 25 stars 8.94 score 115 scripts

statdivlab

corncob:Count Regression for Correlated Observations with the Beta-Binomial

Statistical modeling for correlated count data using the beta-binomial distribution, described in Martin et al. (2020) <doi:10.1214/19-AOAS1283>. It allows for both mean and overdispersion covariates.

Maintained by Amy D Willis. Last updated 6 months ago.

5.8 match 105 stars 9.64 score 248 scripts 1 dependents

bioc

scRepertoire:A toolkit for single-cell immune receptor profiling

scRepertoire is a toolkit for processing and analyzing single-cell T-cell receptor (TCR) and immunoglobulin (Ig). The scRepertoire framework supports use of 10x, AIRR, BD, MiXCR, Omniscope, TRUST4, and WAT3R single-cell formats. The functionality includes basic clonal analyses, repertoire summaries, distance-based clustering and interaction with the popular Seurat and SingleCellExperiment/Bioconductor R workflows.

Maintained by Nick Borcherding. Last updated 2 months ago.

software immunooncology singlecell classification annotation sequencing cpp

5.3 match 326 stars 10.49 score 240 scripts

bioc

DEFormats:Differential gene expression data formats converter

Convert between different data formats used by differential gene expression analysis tools.

Maintained by Andrzej Oleś. Last updated 5 months ago.

immunooncology differentialexpression geneexpression rnaseq sequencing transcription

8.1 match 4 stars 6.82 score 78 scripts 1 dependents

r-simmer

simmer:Discrete-Event Simulation for R

A process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R. It is designed as a generic yet powerful framework. The architecture encloses a robust and fast simulation core written in 'C++' with automatic monitoring capabilities. It provides a rich and flexible R API that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type. Documentation about 'simmer' is provided by several vignettes included in this package, via the paper by Ucar, Smeets & Azcorra (2019, <doi:10.18637/jss.v090.i02>), and the paper by Ucar, Hernández, Serrano & Azcorra (2018, <doi:10.1109/MCOM.2018.1700960>); see 'citation("simmer")' for details.

Maintained by Iñaki Ucar. Last updated 6 months ago.

discrete-event simulation cpp

4.8 match 223 stars 11.47 score 440 scripts 6 dependents

nx10

httpgd:A 'HTTP' Server Graphics Device

A graphics device for R that is accessible via network protocols. This package was created to make it easier to embed live R graphics in integrated development environments and other applications. The included 'HTML/JavaScript' client (plot viewer) aims to provide a better overall user experience when dealing with R graphics. The device asynchronously serves graphics via 'HTTP' and 'WebSockets'.

Maintained by Florian Rupprecht. Last updated 9 hours ago.

cpp

5.0 match 428 stars 11.01 score 280 scripts 1 dependents

knausb

vcfR:Manipulate and Visualize VCF Data

Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software.

Maintained by Brian J. Knaus. Last updated 22 days ago.

genomics population-genetics population-genomics rcpp vcf-data visualization zlib cpp

4.0 match 254 stars 13.59 score 3.1k scripts 19 dependents

bioc

Damsel:Damsel: an end to end analysis of DamID

Damsel provides an end to end analysis of DamID data. Damsel takes bam files from Dam-only control and fusion samples and counts the reads matching to each GATC region. edgeR is utilised to identify regions of enrichment in the fusion relative to the control. Enriched regions are combined into peaks, and are associated with nearby genes. Damsel allows for IGV style plots to be built as the results build, inspired by ggcoverage, and using the functionality and layering ability of ggplot2. Damsel also conducts gene ontology testing with bias correction through goseq, and future versions of Damsel will also incorporate motif enrichment analysis. Overall, Damsel is the first package allowing for an end to end analysis with visual capabilities. The goal of Damsel was to bring all the analysis into one place, and allow for exploratory analysis within R.

Maintained by Caitlin Page. Last updated 5 months ago.

differentialmethylation peakdetection geneprediction genesetenrichment

10.2 match 5.34 score 20 scripts

nsaph-software

CausalGPS:Matching on Generalized Propensity Scores with Continuous Exposures

Provides a framework for estimating causal effects of a continuous exposure using observational data, and implementing matching and weighting on the generalized propensity score. Wu, X., Mealli, F., Kioumourtzoglou, M.A., Dominici, F. and Braun, D., 2022. Matching on generalized propensity scores with continuous exposures. Journal of the American Statistical Association, pp.1-29.

Maintained by Naeem Khoshnevis. Last updated 9 months ago.

cpp openmp

7.1 match 24 stars 7.67 score 39 scripts

bioc

M3Drop:Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

This package fits a model to the pattern of dropouts in single-cell RNASeq data. This model is used as a null to identify significantly variable (i.e. differentially expressed) genes for use in downstream analysis, such as clustering cells. Also includes an method for calculating exact Pearson residuals in UMI-tagged data using a library-size aware negative binomial model.

Maintained by Tallulah Andrews. Last updated 5 months ago.

rnaseq sequencing transcriptomics geneexpression software differentialexpression dimensionreduction featureextraction human-cell-atlas rna-seq single-cell single-cell-rna-seq

6.3 match 29 stars 8.71 score 119 scripts 2 dependents

sn248

sundialr:An Interface to 'SUNDIALS' Ordinary Differential Equation (ODE) Solvers

Provides a way to call the functions in 'SUNDIALS' C ODE solving library (<https://computing.llnl.gov/projects/sundials>). Currently the serial version of ODE solver, 'CVODE', sensitivity calculator 'CVODES' and differential algebraic solver 'IDA' from the 'SUNDIALS' library are implemented. The package requires ODE to be written as an 'R' or 'Rcpp' function and does not require the 'SUNDIALS' library to be installed on the local machine.

Maintained by Satyaprakash Nayak. Last updated 2 months ago.

ode-solver sundials cpp

8.7 match 10 stars 6.26 score 9 scripts

dexter-psychometrics

dexter:Data Management and Analysis of Tests

A system for the management, assessment, and psychometric analysis of data from educational and psychological tests.

Maintained by Jesse Koops. Last updated 5 days ago.

openblas cpp openmp

6.0 match 8 stars 8.97 score 135 scripts 2 dependents

bioc

TADCompare:TADCompare: Identification and characterization of differential TADs

TADCompare is an R package designed to identify and characterize differential Topologically Associated Domains (TADs) between multiple Hi-C contact matrices. It contains functions for finding differential TADs between two datasets, finding differential TADs over time and identifying consensus TADs across multiple matrices. It takes all of the main types of HiC input and returns simple, comprehensive, easy to analyze results.

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing featureextraction clustering

7.7 match 23 stars 7.04 score 10 scripts

open-aims

bayesnec:A Bayesian No-Effect- Concentration (NEC) Algorithm

Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017)<doi:10.18637/jss.v080.i01>; Burkner (2018)<doi:10.32614/RJ-2018-017>; Carpenter 'et al.' (2017)<doi:10.18637/jss.v076.i01> to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating 'ECx' values, but more particularly 'NEC' (see Fox (2010)<doi:10.1016/j.ecoenv.2009.09.012>), 'NSEC' (see Fisher and Fox (2023)<doi:10.1002/etc.5610>), and 'N(S)EC (see Fisher et al. 2023<doi:10.1002/ieam.4809>). A full description of this package can be found in Fisher 'et al.' (2024)<doi:10.18637/jss.v110.i05>. This package expands and supersedes an original version implemented in 'R2jags' (see Su and Yajima (2020)<https://CRAN.R-project.org/package=R2jags>; Fisher et al. (2020)<doi:10.5281/ZENODO.3966864>).

Maintained by Rebecca Fisher. Last updated 7 months ago.

bayesian-inference concentration-response ecotoxicology no-effect-concentration non-linear-decay threshold-derivation toxicology

6.7 match 12 stars 8.11 score 360 scripts

bioc

NBAMSeq:Negative Binomial Additive Model for RNA-Seq Data

High-throughput sequencing experiments followed by differential expression analysis is a widely used approach to detect genomic biomarkers. A fundamental step in differential expression analysis is to model the association between gene counts and covariates of interest. NBAMSeq a flexible statistical model based on the generalized additive model and allows for information sharing across genes in variance estimation.

Maintained by Xu Ren. Last updated 5 months ago.

rnaseq differentialexpression geneexpression sequencing coverage differential-expression gene-expression generalized-additive-models generalized-linear-models negative-binomial-regression splines

11.3 match 2 stars 4.78 score 2 scripts

bioc

dmrseq:Detection and inference of differentially methylated regions from Whole Genome Bisulfite Sequencing

This package implements an approach for scanning the genome to detect and perform accurate inference on differentially methylated regions from Whole Genome Bisulfite Sequencing data. The method is based on comparing detected regions to a pooled null distribution, that can be implemented even when as few as two samples per population are available. Region-level statistics are obtained by fitting a generalized least squares (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions.

Maintained by Keegan Korthauer. Last updated 5 months ago.

immunooncology dnamethylation epigenetics multiplecomparison software sequencing differentialmethylation wholegenome regression functionalgenomics

8.4 match 6.39 score 59 scripts 1 dependents

bioc

GDCRNATools:GDCRNATools: an R/Bioconductor package for integrative analysis of lncRNA, mRNA, and miRNA data in GDC

This is an easy-to-use package for downloading, organizing, and integrative analyzing RNA expression data in GDC with an emphasis on deciphering the lncRNA-mRNA related ceRNA regulatory network in cancer. Three databases of lncRNA-miRNA interactions including spongeScan, starBase, and miRcode, as well as three databases of mRNA-miRNA interactions including miRTarBase, starBase, and miRcode are incorporated into the package for ceRNAs network construction. limma, edgeR, and DESeq2 can be used to identify differentially expressed genes/miRNAs. Functional enrichment analyses including GO, KEGG, and DO can be performed based on the clusterProfiler and DO packages. Both univariate CoxPH and KM survival analyses of multiple genes can be implemented in the package. Besides some routine visualization functions such as volcano plot, bar plot, and KM plot, a few simply shiny apps are developed to facilitate visualization of results on a local webpage.

Maintained by Ruidong Li. Last updated 5 months ago.

immunooncology geneexpression differentialexpression generegulation genetarget networkinference survival visualization genesetenrichment networkenrichment network rnaseq go kegg

9.5 match 5.64 score 44 scripts

cozygene

TCA:Tensor Composition Analysis

Tensor Composition Analysis (TCA) allows the deconvolution of two-dimensional data (features by observations) coming from a mixture of heterogeneous sources into a three-dimensional matrix of signals (features by observations by sources). The TCA framework further allows to test the features in the data for different statistical relations with an outcome of interest while modeling source-specific effects; particularly, it allows to look for statistical relations between source-specific signals and an outcome. For example, TCA can deconvolve bulk tissue-level DNA methylation data (methylation sites by individuals) into a three-dimensional tensor of cell-type-specific methylation levels for each individual (i.e. methylation sites by individuals by cell types) and it allows to detect cell-type-specific statistical relations (associations) with phenotypes. For more details see Rahmani et al. (2019) <DOI:10.1038/s41467-019-11052-9>.

Maintained by Elior Rahmani. Last updated 4 years ago.

7.3 match 18 stars 7.30 score 37 scripts 2 dependents

rstudio

promises:Abstractions for Promise-Based Asynchronous Programming

Provides fundamental abstractions for doing asynchronous programming in R using promises. Asynchronous programming is useful for allowing a single R process to orchestrate multiple tasks in the background while also attending to something else. Semantics are similar to 'JavaScript' promises, but with a syntax that is idiomatic R.

Maintained by Joe Cheng. Last updated 1 months ago.

cpp

3.1 match 204 stars 17.10 score 688 scripts 2.6k dependents

bioc

HybridExpress:Comparative analysis of RNA-seq data for hybrids and their progenitors

HybridExpress can be used to perform comparative transcriptomics analysis of hybrids (or allopolyploids) relative to their progenitor species. The package features functions to perform exploratory analyses of sample grouping, identify differentially expressed genes in hybrids relative to their progenitors, classify genes in expression categories (N = 12) and classes (N = 5), and perform functional analyses. We also provide users with graphical functions for the seamless creation of publication-ready figures that are commonly used in the literature.

Maintained by Fabricio Almeida-Silva. Last updated 5 months ago.

software functionalgenomics geneexpression transcriptomics rnaseq classification differentialexpression gene-expression hybrid polyploidy rna-seq

9.8 match 12 stars 5.38 score 2 scripts

bioc

msmsTests:LC-MS/MS Differential Expression Tests

Statistical tests for label-free LC-MS/MS data by spectral counts, to discover differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package.The three models admit blocking factors to control for nuissance variables.To assure a good level of reproducibility a post-test filter is available, where we may set the minimum effect size considered biologicaly relevant, and the minimum expression of the most abundant condition.

Maintained by Josep Gregori i Font. Last updated 5 months ago.

immunooncology software massspectrometry proteomics

10.4 match 5.03 score 15 scripts 1 dependents

patriciamar

ShinyItemAnalysis:Test and Item Analysis via Shiny

Package including functions and interactive shiny application for the psychometric analysis of educational tests, psychological assessments, health-related and other types of multi-item measurements, or ratings from multiple raters.

Maintained by Patricia Martinkova. Last updated 1 months ago.

assessment differential-item-functioning item-analysis item-response-theory psychometrics shiny

6.7 match 44 stars 7.88 score 105 scripts 3 dependents

shabbychef

madness:Automatic Differentiation of Multivariate Operations

An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via 'forward accumulation'.

Maintained by Steven E. Pav. Last updated 4 years ago.

8.0 match 31 stars 6.59 score 28 scripts 3 dependents

simonlabcode

bakR:Analyze and Compare Nucleotide Recoding RNA Sequencing Datasets

Several implementations of a novel Bayesian hierarchical statistical model of nucleotide recoding RNA-seq experiments (NR-seq; TimeLapse-seq, SLAM-seq, TUC-seq, etc.) for analyzing and comparing NR-seq datasets (see 'Vock and Simon' (2023) <doi:10.1261/rna.079451.122>). NR-seq is a powerful extension of RNA-seq that provides information about the kinetics of RNA metabolism (e.g., RNA degradation rate constants), which is notably lacking in standard RNA-seq data. The statistical model makes maximal use of these high-throughput datasets by sharing information across transcripts to significantly improve uncertainty quantification and increase statistical power. 'bakR' includes a maximally efficient implementation of this model for conservative initial investigations of datasets. 'bakR' also provides more highly powered implementations using the probabilistic programming language 'Stan' to sample from the full posterior distribution. 'bakR' performs multiple-test adjusted statistical inference with the output of these model implementations to help biologists separate signal from background. Methods to automatically visualize key results and detect batch effects are also provided.

Maintained by Isaac Vock. Last updated 4 months ago.

cpp

8.5 match 6 stars 6.12 score 21 scripts

kharchenkolab

conos:Clustering on Network of Samples

Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.

Maintained by Evan Biederstedt. Last updated 1 years ago.

batch-correction scrna-seq single-cell-rna-seq openblas cpp openmp

7.1 match 204 stars 7.32 score 258 scripts