Showing 38 of total 38 results (show query)
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 25 days ago.
sequencingrnaseqchipseqgeneexpressiontranscriptionnormalizationdifferentialexpressionbayesianregressionprincipalcomponentclusteringimmunooncologyopenblascpp
375 stars 16.11 score 17k scripts 115 dependentsbioc
BiocGenerics:S4 generic functions used in Bioconductor
The package defines many S4 generic functions used in Bioconductor.
Maintained by Hervé Pagès. Last updated 2 months ago.
infrastructurebioconductor-packagecore-package
12 stars 14.22 score 612 scripts 2.2k dependentsbioc
SingleCellExperiment:S4 Classes for Single Cell Data
Defines a S4 class for storing data from single-cell experiments. This includes specialized methods to store and retrieve spike-in information, dimensionality reduction coordinates and size factors for each cell, along with the usual metadata for genes and libraries.
Maintained by Davide Risso. Last updated 23 days ago.
immunooncologydatarepresentationdataimportinfrastructuresinglecell
13.53 score 15k scripts 285 dependents
projectmosaic
mosaic:Project MOSAIC Statistics and Mathematics Teaching Utilities
Data sets and utilities from Project MOSAIC (<http://www.mosaic-web.org>) used to teach mathematics, statistics, computation and modeling. Funded by the NSF, Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.
Maintained by Randall Pruim. Last updated 1 years ago.
93 stars 13.32 score 7.2k scripts 7 dependentsbioc
EDASeq:Exploratory Data Analysis and Normalization for RNA-Seq
Numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010).
Maintained by Davide Risso. Last updated 5 months ago.
immunooncologysequencingrnaseqpreprocessingqualitycontroldifferentialexpression
5 stars 10.24 score 594 scripts 9 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 4 days ago.
3 stars 10.06 score 410 scripts 5 dependents
trinker
qdap:Bridging the Gap Between Qualitative Data and Quantitative Analysis
Automates many of the tasks associated with quantitative discourse analysis of transcripts containing discourse including frequency counts of sentence types, words, sentences, turns of talk, syllables and other assorted analysis tasks. The package provides parsing tools for preparing transcript data. Many functions enable the user to aggregate data by any number of grouping variables, providing analysis and seamless integration with other R packages that undertake higher level analysis and visualization of text. This affords the user a more efficient and targeted analysis. 'qdap' is designed for transcript analysis, however, many functions are applicable to other areas of Text Mining/ Natural Language Processing.
Maintained by Tyler Rinker. Last updated 5 years ago.
qdapquantitative-discourse-analysistext-analysistext-miningtext-plottingopenjdk
176 stars 9.61 score 1.3k scripts 3 dependentsbioc
SpatialFeatureExperiment:Integrating SpatialExperiment with Simple Features in sf
A new S4 class integrating Simple Features with the R package sf to bring geospatial data analysis methods based on vector data to spatial transcriptomics. Also implements management of spatial neighborhood graphs and geometric operations. This pakage builds upon SpatialExperiment and SingleCellExperiment, hence methods for these parent classes can still be used.
Maintained by Lambda Moses. Last updated 2 months ago.
datarepresentationtranscriptomicsspatial
49 stars 9.40 score 322 scripts 1 dependentsbioc
OUTRIDER:OUTRIDER - OUTlier in RNA-Seq fInDER
Identification of aberrant gene expression in RNA-seq data. Read count expectations are modeled by an autoencoder to control for confounders in the data. Given these expectations, the RNA-seq read counts are assumed to follow a negative binomial distribution with a gene-specific dispersion. Outliers are then identified as read counts that significantly deviate from this distribution. Furthermore, OUTRIDER provides useful plotting functions to analyze and visualize the results.
Maintained by Christian Mertes. Last updated 5 months ago.
immunooncologyrnaseqtranscriptomicsalignmentsequencinggeneexpressiongeneticscount-datadiagnosticsexpression-analysismendelian-geneticsoutlier-detectionrna-seqopenblascpp
50 stars 9.07 score 110 scripts 1 dependents
cmmr
rbiom:Read/Write, Analyze, and Visualize 'BIOM' Data
A toolkit for working with Biological Observation Matrix ('BIOM') files. Read/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and beta diversity (including 'UniFrac'). Summarize counts by taxonomic level. Subset based on metadata. Generate visualizations and statistical analyses. CPU intensive operations are coded in C for speed.
Maintained by Daniel P. Smith. Last updated 12 days ago.
15 stars 9.07 score 117 scripts 6 dependentsbioc
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.
rnaseqdifferentialexpressionnormalizationpreprocessingqualitycontrolrna-seqstatistical-engineering
11 stars 7.77 score 48 scripts 1 dependentsbioc
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 30 days ago.
immunooncologysequencingrnaseqdifferentialexpressionalternativesplicingdifferentialsplicinggeneexpressionvisualization
7.75 score 330 scripts 6 dependentsbioc
chromVAR:Chromatin Variation Across Regions
Determine variation in chromatin accessibility across sets of annotations or peaks. Designed primarily for single-cell or sparse chromatin accessibility data, e.g. from scATAC-seq or sparse bulk ATAC or DNAse-seq experiments.
Maintained by Alicia Schep. Last updated 5 months ago.
singlecellsequencinggeneregulationimmunooncologycpp
7.31 score 772 scripts
darunabas
phyloregion:Biogeographic Regionalization and Macroecology
Computational infrastructure for biogeography, community ecology, and biodiversity conservation (Daru et al. 2020) <doi:10.1111/2041-210X.13478>. It is based on the methods described in Daru et al. (2020) <doi:10.1038/s41467-020-15921-6>. The original conceptual work is described in Daru et al. (2017) <doi:10.1016/j.tree.2017.08.013> on patterns and processes of biogeographical regionalization. Additionally, the package contains fast and efficient functions to compute more standard conservation measures such as phylogenetic diversity, phylogenetic endemism, evolutionary distinctiveness and global endangerment, as well as compositional turnover (e.g., beta diversity).
Maintained by Barnabas H. Daru. Last updated 5 months ago.
18 stars 7.21 score 50 scripts 1 dependentsprojectmosaic
mosaicCore:Common Utilities for Other MOSAIC-Family Packages
Common utilities used in other MOSAIC-family packages are collected here.
Maintained by Randall Pruim. Last updated 1 years ago.
1 stars 7.07 score 113 scripts 26 dependentsbioc
isomiRs:Analyze isomiRs and miRNAs from small RNA-seq
Characterization of miRNAs and isomiRs, clustering and differential expression.
Maintained by Lorena Pantano. Last updated 5 months ago.
mirnarnaseqdifferentialexpressionclusteringimmunooncologyanalyze-isomirsbioconductorisomirs
8 stars 6.97 score 43 scriptsbioc
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.
immunooncologysnpalternativesplicingdifferentialsplicinggeneticsrnaseqsequencingworkflowstepmultiplecomparisongeneexpressiondifferentialexpression
6.91 score 136 scripts 2 dependentsbioc
maser:Mapping Alternative Splicing Events to pRoteins
This package provides functionalities for downstream analysis, annotation and visualizaton of alternative splicing events generated by rMATS.
Maintained by Diogo F.T. Veiga. Last updated 5 months ago.
alternativesplicingtranscriptomicsvisualization
17 stars 6.74 score 18 scripts
fabrice-rossi
mixvlmc:Variable Length Markov Chains with Covariates
Estimates Variable Length Markov Chains (VLMC) models and VLMC with covariates models from discrete sequences. Supports model selection via information criteria and simulation of new sequences from an estimated model. See Bühlmann, P. and Wyner, A. J. (1999) <doi:10.1214/aos/1018031204> for VLMC and Zanin Zambom, A., Kim, S. and Lopes Garcia, N. (2022) <doi:10.1111/jtsa.12615> for VLMC with covariates.
Maintained by Fabrice Rossi. Last updated 11 months ago.
machine-learningmarkov-chainmarkov-modelstatisticstime-seriescpp
2 stars 6.23 score 20 scriptsbioc
TCseq:Time course sequencing data analysis
Quantitative and differential analysis of epigenomic and transcriptomic time course sequencing data, clustering analysis and visualization of the temporal patterns of time course data.
Maintained by Mengjun Wu. Last updated 5 months ago.
epigeneticstimecoursesequencingchipseqrnaseqdifferentialexpressionclusteringvisualization
5.92 score 28 scripts 1 dependentsbioc
SGSeq:Splice event prediction and quantification from RNA-seq data
SGSeq is a software package for analyzing splice events from RNA-seq data. Input data are RNA-seq reads mapped to a reference genome in BAM format. Genes are represented as a splice graph, which can be obtained from existing annotation or predicted from the mapped sequence reads. Splice events are identified from the graph and are quantified locally using structurally compatible reads at the start or end of each splice variant. The software includes functions for splice event prediction, quantification, visualization and interpretation.
Maintained by Leonard Goldstein. Last updated 5 months ago.
alternativesplicingimmunooncologyrnaseqtranscription
5.91 score 45 scripts 3 dependentsbioc
autonomics:Unified Statistical Modeling of Omics Data
This package unifies access to Statistal Modeling of Omics Data. Across linear modeling engines (lm, lme, lmer, limma, and wilcoxon). Across coding systems (treatment, difference, deviation, etc). Across model formulae (with/without intercept, random effect, interaction or nesting). Across omics platforms (microarray, rnaseq, msproteomics, affinity proteomics, metabolomics). Across projection methods (pca, pls, sma, lda, spls, opls). Across clustering methods (hclust, pam, cmeans). It provides a fast enrichment analysis implementation. And an intuitive contrastogram visualisation to summarize contrast effects in complex designs.
Maintained by Aditya Bhagwat. Last updated 2 months ago.
softwaredataimportpreprocessingdimensionreductionprincipalcomponentregressiondifferentialexpressiongenesetenrichmenttranscriptomicstranscriptiongeneexpressionrnaseqmicroarrayproteomicsmetabolomicsmassspectrometry
5.89 score 5 scripts
dgerlanc
backtest:Exploring Portfolio-Based Conjectures About Financial Instruments
The backtest package provides facilities for exploring portfolio-based conjectures about financial instruments (stocks, bonds, swaps, options, et cetera).
Maintained by Daniel Gerlanc. Last updated 10 years ago.
20 stars 5.52 score 33 scripts
s87jackson
rfars:Download and Analyze Crash Data
Download crash data from the National Highway Traffic Safety Administration and prepare it for research.
Maintained by Steve Jackson. Last updated 12 months ago.
crashfatalitiesofficial-statisticstransportation
10 stars 5.35 score 15 scriptsbioc
PhIPData:Container for PhIP-Seq Experiments
PhIPData defines an S4 class for phage-immunoprecipitation sequencing (PhIP-seq) experiments. Buliding upon the RangedSummarizedExperiment class, PhIPData enables users to coordinate metadata with experimental data in analyses. Additionally, PhIPData provides specialized methods to subset and identify beads-only samples, subset objects using virus aliases, and use existing peptide libraries to populate object parameters.
Maintained by Athena Chen. Last updated 5 months ago.
infrastructuredatarepresentationsequencingcoverage
6 stars 5.26 score 6 scripts 1 dependents
ropensci
neotoma:Access to the Neotoma Paleoecological Database Through R
NOTE: This package is deprecated. Please use the neotoma2 package described at https://github.com/NeotomaDB/neotoma2. Access paleoecological datasets from the Neotoma Paleoecological Database using the published API (<http://wnapi.neotomadb.org/>), only containing datasets uploaded prior to June 2020. The functions in this package access various pre-built API functions and attempt to return the results from Neotoma in a usable format for researchers and the public.
Maintained by Simon J. Goring. Last updated 2 years ago.
neotomaneotoma-apisneotoma-databasensfpaleoecology
30 stars 5.04 score 145 scripts
jmbarbone
mark:Miscellaneous, Analytic R Kernels
Miscellaneous functions and wrappers for development in other packages created, maintained by Jordan Mark Barbone.
Maintained by Jordan Mark Barbone. Last updated 2 months ago.
6 stars 4.95 score 9 scriptsbioc
mariner:Mariner: Explore the Hi-Cs
Tools for manipulating paired ranges and working with Hi-C data in R. Functionality includes manipulating/merging paired regions, generating paired ranges, extracting/aggregating interactions from `.hic` files, and visualizing the results. Designed for compatibility with plotgardener for visualization.
Maintained by Eric Davis. Last updated 5 months ago.
functionalgenomicsvisualizationhic
4.89 score 77 scriptsbioc
flowFP:Fingerprinting for Flow Cytometry
Fingerprint generation of flow cytometry data, used to facilitate the application of machine learning and datamining tools for flow cytometry.
Maintained by Herb Holyst. Last updated 5 months ago.
flowcytometrycellbasedassaysclusteringvisualization
4.72 score 11 scripts 2 dependents
robinhankin
MM:The Multiplicative Multinomial Distribution
Various utilities for the Multiplicative Multinomial distribution.
Maintained by Robin K. S. Hankin. Last updated 11 months ago.
4.64 score 22 scriptsbioc
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.
4.62 score 1 scripts 1 dependentsbioc
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.
sequencingrnaseqgenesetenrichmentgeneexpressiondifferentialexpressiondifferentialsplicingimmunooncology
4.34 score 11 scriptsbioc
IntEREst:Intron-Exon Retention Estimator
This package performs Intron-Exon Retention analysis on RNA-seq data (.bam files).
Maintained by Ali Oghabian. Last updated 2 days ago.
softwarealternativesplicingcoveragedifferentialsplicingsequencingrnaseqalignmentnormalizationdifferentialexpressionimmunooncology
4.16 score 12 scriptsbioc
ccfindR:Cancer Clone Finder
A collection of tools for cancer genomic data clustering analyses, including those for single cell RNA-seq. Cell clustering and feature gene selection analysis employ Bayesian (and maximum likelihood) non-negative matrix factorization (NMF) algorithm. Input data set consists of RNA count matrix, gene, and cell bar code annotations. Analysis outputs are factor matrices for multiple ranks and marginal likelihood values for each rank. The package includes utilities for downstream analyses, including meta-gene identification, visualization, and construction of rank-based trees for clusters.
Maintained by Jun Woo. Last updated 5 months ago.
transcriptomicssinglecellimmunooncologybayesianclusteringgslcpp
4.00 score 9 scriptsbioc
segmenter:Perform Chromatin Segmentation Analysis in R by Calling ChromHMM
Chromatin segmentation analysis transforms ChIP-seq data into signals over the genome. The latter represents the observed states in a multivariate Markov model to predict the chromatin's underlying states. ChromHMM, written in Java, integrates histone modification datasets to learn the chromatin states de-novo. The goal of this package is to call chromHMM from within R, capture the output files in an S4 object and interface to other relevant Bioconductor analysis tools. In addition, segmenter provides functions to test, select and visualize the output of the segmentation.
Maintained by Mahmoud Ahmed. Last updated 5 months ago.
softwarehistonemodificationbioconductorchromhmmsegmentation-an
4 stars 3.60 score 9 scripts
oswaldomuron
Kifidi:Summary Table and Means Plots
Optimized for handling complex datasets in environmental and ecological research, this package offers functionality that is not fully met by general-purpose packages. It provides two key functions, 'summarize_data()', which summarizes datasets, and 'plot_means()', which creates plots with error bars. The 'plot_means()' function incorporates error bars by default, allowing quick visualization of uncertainties, crucial in ecological studies. It also streamlines workflows for grouped datasets (e.g., by species or treatment), making it particularly user-friendly and reducing the complexity and time required for data summarization and visualization.
Maintained by Oswald Omuron. Last updated 4 months ago.
3.48 score 1 scriptsbioc
Rmmquant:RNA-Seq multi-mapping Reads Quantification Tool
RNA-Seq is currently used routinely, and it provides accurate information on gene transcription. However, the method cannot accurately estimate duplicated genes expression. Several strategies have been previously used, but all of them provide biased results. With Rmmquant, if a read maps at different positions, the tool detects that the corresponding genes are duplicated; it merges the genes and creates a merged gene. The counts of ambiguous reads is then based on the input genes and the merged genes. Rmmquant is a drop-in replacement of the widely used tools findOverlaps and featureCounts that handles multi-mapping reads in an unabiased way.
Maintained by Zytnicki Matthias. Last updated 5 months ago.
geneexpressiontranscriptionzlibcpp
3.30 score 5 scripts