R-universe search: topic:software

bioc

ComplexHeatmap:Make Complex Heatmaps

Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports various annotation graphics.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization sequencing clustering complex-heatmaps heatmap

1.4k stars 16.94 score 16k scripts 155 dependents

bioc

ggtree:an R package for visualization of tree and annotation data

'ggtree' extends the 'ggplot2' plotting system which implemented the grammar of graphics. 'ggtree' is designed for visualization and annotation of phylogenetic trees and other tree-like structures with their annotation data.

Maintained by Guangchuang Yu. Last updated 5 months ago.

alignment annotation clustering dataimport multiplesequencealignment phylogenetics reproducibleresearch software visualization annotations ggplot2 phylogenetic-trees

871 stars 16.83 score 5.1k scripts 109 dependents

klausvigo

phangorn:Phylogenetic Reconstruction and Analysis

Allows for estimation of phylogenetic trees and networks using Maximum Likelihood, Maximum Parsimony, distance methods and Hadamard conjugation (Schliep 2011). Offers methods for tree comparison, model selection and visualization of phylogenetic networks as described in Schliep et al. (2017).

Maintained by Klaus Schliep. Last updated 20 hours ago.

software technology qualitycontrol phylogenetic-analysis phylogenetics openblas cpp

206 stars 16.70 score 2.5k scripts 135 dependents

bioc

enrichplot:Visualization of Functional Enrichment Result

The 'enrichplot' package implements several visualization methods for interpreting functional enrichment results obtained from ORA or GSEA analysis. It is mainly designed to work with the 'clusterProfiler' package suite. All the visualization methods are developed based on 'ggplot2' graphics.

Maintained by Guangchuang Yu. Last updated 3 months ago.

annotation genesetenrichment go kegg pathways software visualization enrichment-analysis pathway-analysis

239 stars 15.71 score 3.1k scripts 58 dependents

bioc

DOSE:Disease Ontology Semantic and Enrichment analysis

This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.

Maintained by Guangchuang Yu. Last updated 5 months ago.

annotation visualization multiplecomparison genesetenrichment pathways software disease-ontology enrichment-analysis semantic-similarity

119 stars 14.97 score 2.0k scripts 61 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 1 months ago.

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

310 stars 14.47 score 1.6k scripts 6 dependents

bioc

GOSemSim:GO-terms Semantic Similarity Measures

The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters. GOSemSim implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively.

Maintained by Guangchuang Yu. Last updated 5 months ago.

annotation go clustering pathways network software bioinformatics gene-ontology semantic-similarity cpp

63 stars 14.12 score 708 scripts 68 dependents

bioc

scran:Methods for Single-Cell RNA-Seq Data Analysis

Implements miscellaneous functions for interpretation of single-cell RNA-seq data. Methods are provided for assignment of cell cycle phase, detection of highly variable and significantly correlated genes, identification of marker genes, and other common tasks in routine single-cell analysis workflows.

Maintained by Aaron Lun. Last updated 5 months ago.

immunooncology normalization sequencing rnaseq software geneexpression transcriptomics singlecell clustering bioconductor-package human-cell-atlas single-cell-rna-seq openblas cpp

41 stars 13.05 score 7.6k scripts 37 dependents

bioc

ChIPseeker:ChIPseeker for ChIP peak Annotation, Comparison, and Visualization

This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets, and incorporate GEO database for user to compare the own dataset with those deposited in database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes.

Maintained by Guangchuang Yu. Last updated 5 months ago.

annotation chipseq software visualization multiplecomparison atac-seq chip-seq comparison epigenetics epigenomics

233 stars 13.05 score 1.6k scripts 5 dependents

bioc

SingleR:Reference-Based Single-Cell RNA-Seq Annotation

Performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer the cell of origin of each single cell independently.

Maintained by Aaron Lun. Last updated 1 months ago.

software singlecell geneexpression transcriptomics classification clustering annotation bioconductor singler cpp

184 stars 12.83 score 2.1k scripts 2 dependents

ropensci

treeio:Base Classes and Functions for Phylogenetic Tree Input and Output

'treeio' is an R package to make it easier to import and store phylogenetic tree with associated data; and to link external data from different sources to phylogeny. It also supports exporting phylogenetic tree with heterogeneous associated data to a single tree file and can be served as a platform for merging tree with associated data and converting file formats.

Maintained by Guangchuang Yu. Last updated 5 months ago.

software annotation clustering dataimport datarepresentation alignment multiplesequencealignment phylogenetics exporter parser phylogenetic-trees

102 stars 12.46 score 1.3k scripts 122 dependents

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 12 days ago.

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

111 stars 12.16 score 1.0k scripts 4 dependents

bioc

BiocSingular:Singular Value Decomposition for Bioconductor Packages

Implements exact and approximate methods for singular value decomposition and principal components analysis, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Where possible, parallelization is achieved using the BiocParallel framework.

Maintained by Aaron Lun. Last updated 5 months ago.

software dimensionreduction principalcomponent bioconductor-package human-cell-atlas singular-value-decomposition cpp

7 stars 12.10 score 1.2k scripts 103 dependents

bioc

slingshot:Tools for ordering single-cell sequencing

Provides functions for inferring continuous, branching lineage structures in low-dimensional data. Slingshot was designed to model developmental trajectories in single-cell RNA sequencing data and serve as a component in an analysis pipeline after dimensionality reduction and clustering. It is flexible enough to handle arbitrarily many branching events and allows for the incorporation of prior knowledge through supervised graph construction.

Maintained by Kelly Street. Last updated 5 months ago.

clustering differentialexpression geneexpression rnaseq sequencing software singlecell transcriptomics visualization

283 stars 12.01 score 1.0k scripts 4 dependents

bioc

sparseMatrixStats:Summary Statistics for Rows and Columns of Sparse Matrices

High performance functions for row and column operations on sparse matrices. For example: col / rowMeans2, col / rowMedians, col / rowVars etc. Currently, the optimizations are limited to data in the column sparse format. This package is inspired by the matrixStats package by Henrik Bengtsson.

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

infrastructure software datarepresentation cpp

54 stars 11.98 score 174 scripts 130 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

69 stars 11.90 score 494 scripts 7 dependents

bioc

DelayedMatrixStats:Functions that Apply to Rows and Columns of 'DelayedMatrix' Objects

A port of the 'matrixStats' API for use with DelayedMatrix objects from the 'DelayedArray' package. High-performing functions operating on rows and columns of DelayedMatrix objects, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.

Maintained by Peter Hickey. Last updated 3 months ago.

infrastructure datarepresentation software

16 stars 11.86 score 211 scripts 112 dependents

msberends

AMR:Antimicrobial Resistance Data Analysis

Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by using evidence-based methods, as described in <doi:10.18637/jss.v104.i03>.

Maintained by Matthijs S. Berends. Last updated 18 hours ago.

amr antimicrobial-data epidemiology microbiology software

95 stars 11.83 score 182 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 3 months ago.

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

7 stars 11.69 score 1.1k scripts 3 dependents

bioc

MatrixGenerics:S4 Generic Summary Statistic Functions that Operate on Matrix-Like Objects

S4 generic functions modeled after the 'matrixStats' API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. Other package developers can import this package and handle a different matrix implementations without worrying about incompatibilities.

Maintained by Peter Hickey. Last updated 3 months ago.

infrastructure software bioconductor-package core-package

12 stars 11.64 score 129 scripts 1.3k dependents

bioc

mia:Microbiome analysis

mia implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.

Maintained by Tuomas Borman. Last updated 15 days ago.

microbiome software dataimport analysis bioconductor

52 stars 11.50 score 316 scripts 5 dependents

bioc

destiny:Creates diffusion maps

Create and plot diffusion maps.

Maintained by Philipp Angerer. Last updated 4 months ago.

cellbiology cellbasedassays clustering software visualization diffusion-maps dimensionality-reduction cpp

82 stars 11.44 score 792 scripts 1 dependents

bioc

PharmacoGx:Analysis of Large-Scale Pharmacogenomic Data

Contains a set of functions to perform large-scale analysis of pharmaco-genomic data. These include the PharmacoSet object for storing the results of pharmacogenomic experiments, as well as a number of functions for computing common summaries of drug-dose response and correlating them with the molecular features in a cancer cell-line.

Maintained by Benjamin Haibe-Kains. Last updated 3 months ago.

geneexpression pharmacogenetics pharmacogenomics software classification datasets pharmacogenomic pharmacogx cpp

68 stars 11.39 score 442 scripts 3 dependents

bioc

BiocStyle:Standard styles for vignettes and other Bioconductor documents

Provides standard formatting styles for Bioconductor PDF and HTML documents. Package vignettes illustrate use and functionality.

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

software bioconductor-package core-package

12 stars 11.31 score 1.2k scripts 47 dependents

bioc

decoupleR:decoupleR: Ensemble of computational methods to infer biological activities from omics data

Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.

Maintained by Pau Badia-i-Mompel. Last updated 5 months ago.

differentialexpression functionalgenomics geneexpression generegulation network software statisticalmethod transcription

230 stars 11.27 score 316 scripts 3 dependents

bioc

scater:Single-Cell Analysis Toolkit for Gene Expression Data in R

A collection of tools for doing various analyses of single-cell RNA-seq gene expression data, with a focus on quality control and visualization.

Maintained by Alan OCallaghan. Last updated 22 days ago.

immunooncology singlecell rnaseq qualitycontrol preprocessing normalization visualization dimensionreduction transcriptomics geneexpression sequencing software dataimport datarepresentation infrastructure coverage

11.07 score 12k scripts 43 dependents

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

133 stars 11.03 score 532 scripts 3 dependents

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

67 stars 10.99 score 362 scripts 2 dependents

bioc

infercnv:Infer Copy Number Variation from Single-Cell RNA-Seq Data

Using single-cell RNA-Seq expression to visualize CNV in cells.

Maintained by Christophe Georgescu. Last updated 5 months ago.

software copynumbervariation variantdetection structuralvariation genomicvariation genetics transcriptomics statisticalmethod bayesian hiddenmarkovmodel singlecell jags cpp

601 stars 10.92 score 674 scripts

bioc

EnrichedHeatmap:Making Enriched Heatmaps

Enriched heatmap is a special type of heatmap which visualizes the enrichment of genomic signals on specific target regions. Here we implement enriched heatmap by ComplexHeatmap package. Since this type of heatmap is just a normal heatmap but with some special settings, with the functionality of ComplexHeatmap, it would be much easier to customize the heatmap as well as concatenating to a list of heatmaps to show correspondance between different data sources.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization sequencing genomeannotation coverage cpp

190 stars 10.87 score 330 scripts 1 dependents

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 13 days ago.

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

120 stars 10.79 score 406 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

184 stars 10.74 score 686 scripts 1 dependents

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

28 stars 10.70 score 424 scripts 3 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 1 months ago.

immunooncology software sequencing riboseq rnaseq functionalgenomics coverage alignment dataimport cpp

33 stars 10.56 score 115 scripts 2 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

362 stars 10.49 score 340 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 10 days ago.

software immunooncology singlecell classification annotation sequencing cpp

327 stars 10.42 score 240 scripts

ssnn-airr

alakazam:Immunoglobulin Clonal Lineage and Diversity Analysis

Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.

Maintained by Susanna Marquez. Last updated 3 months ago.

software annotationdata cpp

10.33 score 424 scripts 7 dependents

bioc

Cardinal:A mass spectrometry imaging toolbox for statistical analysis

Implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.

Maintained by Kylie Ariel Bemis. Last updated 3 months ago.

software infrastructure proteomics lipidomics massspectrometry imagingmassspectrometry immunooncology normalization clustering classification regression

48 stars 10.32 score 200 scripts

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

43 stars 10.21 score 190 scripts 6 dependents

bioc

scuttle:Single-Cell RNA-Seq Analysis Utilities

Provides basic utility functions for performing single-cell analyses, focusing on simple normalization, quality control and data transformations. Also provides some helper functions to assist development of other packages.

Maintained by Aaron Lun. Last updated 5 months ago.

immunooncology singlecell rnaseq qualitycontrol preprocessing normalization transcriptomics geneexpression sequencing software dataimport openblas cpp

10.21 score 1.7k scripts 80 dependents

bioc

AnnotationFilter:Facilities for Filtering Bioconductor Annotation Resources

This package provides class and other infrastructure to implement filters for manipulating Bioconductor annotation resources. The filters will be used by ensembldb, Organism.dplyr, and other packages.

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

annotation infrastructure software bioconductor-package core-package

5 stars 10.19 score 45 scripts 160 dependents

bioc

cBioPortalData:Exposes and Makes Available Data from the cBioPortal Web Resources

The cBioPortalData R package accesses study datasets from the cBio Cancer Genomics Portal. It accesses the data either from the pre-packaged zip / tar files or from the API interface that was recently implemented by the cBioPortal Data Team. The package can provide data in either tabular format or with MultiAssayExperiment object that uses familiar Bioconductor data representations.

Maintained by Marcel Ramos. Last updated 8 days ago.

software infrastructure thirdpartyclient bioconductor-package nci-itcr u24ca289073

33 stars 10.17 score 147 scripts 4 dependents

bioc

BASiCS:Bayesian Analysis of Single-Cell Sequencing data

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model to perform statistical analyses of single-cell RNA sequencing datasets in the context of supervised experiments (where the groups of cells of interest are known a priori, e.g. experimental conditions or cell types). BASiCS performs built-in data normalisation (global scaling) and technical noise quantification (based on spike-in genes). BASiCS provides an intuitive detection criterion for highly (or lowly) variable genes within a single group of cells. Additionally, BASiCS can compare gene expression patterns between two or more pre-specified groups of cells. Unlike traditional differential expression tools, BASiCS quantifies changes in expression that lie beyond comparisons of means, also allowing the study of changes in cell-to-cell heterogeneity. The latter can be quantified via a biological over-dispersion parameter that measures the excess of variability that is observed with respect to Poisson sampling noise, after normalisation and technical noise removal. Due to the strong mean/over-dispersion confounding that is typically observed for scRNA-seq datasets, BASiCS also tests for changes in residual over-dispersion, defined by residual values with respect to a global mean/over-dispersion trend.

Maintained by Catalina Vallejos. Last updated 5 months ago.

immunooncology normalization sequencing rnaseq software geneexpression transcriptomics singlecell differentialexpression bayesian cellbiology bioconductor-package gene-expression rcpp rcpparmadillo scrna-seq single-cell openblas cpp openmp

83 stars 10.14 score 368 scripts 1 dependents

bioc

SC3:Single-Cell Consensus Clustering

A tool for unsupervised clustering and analysis of single cell RNA-Seq data.

Maintained by Vladimir Kiselev. Last updated 5 months ago.

immunooncology singlecell software classification clustering dimensionreduction supportvectormachine rnaseq visualization transcriptomics datarepresentation gui differentialexpression transcription bioconductor-package human-cell-atlas single-cell-rna-seq openblas cpp

125 stars 10.10 score 374 scripts 1 dependents

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

251 stars 10.06 score 440 scripts

bioc

singscore:Rank-based single-sample gene set scoring method

A simple single-sample gene signature scoring method that uses rank-based statistics to analyze the sample's gene expression profile. It scores the expression activities of gene sets at a single-sample level.

Maintained by Malvika Kharbanda. Last updated 5 months ago.

software geneexpression genesetenrichment bioinformatics

41 stars 10.03 score 124 scripts 4 dependents

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 4 months ago.

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

42 stars 10.03 score 78 scripts 6 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 2 months ago.

immunooncology flowcytometry proteomics singlecell cellbasedassays cellbiology clustering featureextraction software

20 stars 9.98 score 225 scripts 5 dependents

bioc

goseq:Gene Ontology analyser for RNA-seq and other length biased data

Detects Gene Ontology and/or other user defined categories which are over/under represented in RNA-seq data.

Maintained by Federico Marini. Last updated 5 months ago.

immunooncology sequencing go geneexpression transcription rnaseq differentialexpression annotation genesetenrichment kegg pathways software

2 stars 9.97 score 636 scripts 9 dependents

bioc

rGREAT:GREAT Analysis - Functional Enrichment on Genomic Regions

GREAT (Genomic Regions Enrichment of Annotations Tool) is a type of functional enrichment analysis directly performed on genomic regions. This package implements the GREAT algorithm (the local GREAT analysis), also it supports directly interacting with the GREAT web service (the online GREAT analysis). Both analysis can be viewed by a Shiny application. rGREAT by default supports more than 600 organisms and a large number of gene set collections, as well as self-provided gene sets and organisms from users. Additionally, it implements a general method for dealing with background regions.

Maintained by Zuguang Gu. Last updated 16 days ago.

genesetenrichment go pathways software sequencing wholegenome genomeannotation coverage cpp

86 stars 9.96 score 320 scripts 1 dependents

bioc

splatter:Simple Simulation of Single-cell RNA Sequencing Data

Splatter is a package for the simulation of single-cell RNA sequencing count data. It provides a simple interface for creating complex simulations that are reproducible and well-documented. Parameters can be estimated from real data and functions are provided for comparing real and simulated datasets.

Maintained by Luke Zappia. Last updated 4 months ago.

singlecell rnaseq transcriptomics geneexpression sequencing software immunooncology bioconductor bioinformatics scrna-seq simulation

224 stars 9.92 score 424 scripts 1 dependents

bioc

RUVSeq:Remove Unwanted Variation from RNA-Seq Data

This package implements the remove unwanted variation (RUV) methods of Risso et al. (2014) for the normalization of RNA-Seq read counts between samples.

Maintained by Davide Risso. Last updated 5 months ago.

immunooncology differentialexpression preprocessing rnaseq software

13 stars 9.91 score 482 scripts 5 dependents

bioc

OmnipathR:OmniPath web service client and more

A client for the OmniPath web service (https://www.omnipathdb.org) and many other resources. It also includes functions to transform and pretty print some of the downloaded data, functions to access a number of other resources such as BioPlex, ConsensusPathDB, EVEX, Gene Ontology, Guide to Pharmacology (IUPHAR/BPS), Harmonizome, HTRIdb, Human Phenotype Ontology, InWeb InBioMap, KEGG Pathway, Pathway Commons, Ramilowski et al. 2015, RegNetwork, ReMap, TF census, TRRUST and Vinayagam et al. 2011. Furthermore, OmnipathR features a close integration with the NicheNet method for ligand activity prediction from transcriptomics data, and its R implementation `nichenetr` (available only on github).

Maintained by Denes Turei. Last updated 1 months ago.

graphandnetwork network pathways software thirdpartyclient dataimport datarepresentation genesignaling generegulation systemsbiology transcriptomics singlecell annotation kegg complexes enzyme-ptm networks networks-biology omnipath proteins quarto

130 stars 9.90 score 226 scripts 2 dependents

bioc

PureCN:Copy number calling and SNV classification using targeted short read sequencing

This package estimates tumor purity, copy number, and loss of heterozygosity (LOH), and classifies single nucleotide variants (SNVs) by somatic status and clonality. PureCN is designed for targeted short read sequencing data, integrates well with standard somatic variant detection and copy number pipelines, and has support for tumor samples without matching normal samples.

Maintained by Markus Riester. Last updated 15 hours ago.

copynumbervariation software sequencing variantannotation variantdetection coverage immunooncology bioconductor-package cell-free-dna copy-number loh tumor-heterogeneity tumor-mutational-burden tumor-purity

132 stars 9.88 score 40 scripts

bioc

annotatr:Annotation of Genomic Regions to Genomic Annotations

Given a set of genomic sites/regions (e.g. ChIP-seq peaks, CpGs, differentially methylated CpGs or regions, SNPs, etc.) it is often of interest to investigate the intersecting genomic annotations. Such annotations include those relating to gene models (promoters, 5'UTRs, exons, introns, and 3'UTRs), CpGs (CpG islands, CpG shores, CpG shelves), or regulatory sequences such as enhancers. The annotatr package provides an easy way to summarize and visualize the intersection of genomic sites/regions with genomic annotations.

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

software annotation genomeannotation functionalgenomics visualization genome-annotation

26 stars 9.76 score 246 scripts 5 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

186 stars 9.70 score 126 scripts 1 dependents

bioc

TCGAutils:TCGA utility functions for data management

A suite of helper functions for checking and manipulating TCGA data including data obtained from the curatedTCGAData experiment package. These functions aim to simplify and make working with TCGA data more manageable. Exported functions include those that import data from flat files into Bioconductor objects, convert row annotations, and identifier translation via the GDC API.

Maintained by Marcel Ramos. Last updated 3 months ago.

software workflowstep preprocessing dataimport bioconductor-package tcga u24ca289073 utilities

27 stars 9.66 score 210 scripts 10 dependents

bioc

clusterExperiment:Compare Clusterings for Single-Cell Sequencing

Provides functionality for running and comparing many different clusterings of single-cell sequencing data or other large mRNA Expression data sets.

Maintained by Elizabeth Purdom. Last updated 5 months ago.

clustering rnaseq sequencing software singlecell cpp

38 stars 9.62 score 192 scripts 1 dependents

bioc

cytomapper:Visualization of highly multiplexed imaging data in R

Highly multiplexed imaging acquires the single-cell expression of selected proteins in a spatially-resolved fashion. These measurements can be visualised across multiple length-scales. First, pixel-level intensities represent the spatial distributions of feature expression with highest resolution. Second, after segmentation, expression values or cell-level metadata (e.g. cell-type information) can be visualised on segmented cell areas. This package contains functions for the visualisation of multiplexed read-outs and cell-level information obtained by multiplexed imaging technologies. The main functions of this package allow 1. the visualisation of pixel-level information across multiple channels, 2. the display of cell-level information (expression and/or metadata) on segmentation masks and 3. gating and visualisation of single cells.

Maintained by Lasse Meyer. Last updated 5 months ago.

immunooncology software singlecell onechannel twochannel multiplecomparison normalization dataimport bioimaging imaging-mass-cytometry single-cell spatial-analysis

32 stars 9.61 score 354 scripts 5 dependents

bioc

recount:Explore and download data from the recount project

Explore and download data from the recount project available at https://jhubiostatistics.shinyapps.io/recount/. Using the recount package you can download RangedSummarizedExperiment objects at the gene, exon or exon-exon junctions level, the raw counts, the phenotype metadata used, the urls to the sample coverage bigWig files or the mean coverage bigWig file for a particular study. The RangedSummarizedExperiment objects can be used by different packages for performing differential expression analysis. Using http://bioconductor.org/packages/derfinder you can perform annotation-agnostic differential expression analyses with the data from the recount project as described at http://www.nature.com/nbt/journal/v35/n4/full/nbt.3838.html.

Maintained by Leonardo Collado-Torres. Last updated 4 months ago.

coverage differentialexpression geneexpression rnaseq sequencing software dataimport immunooncology annotation-agnostic bioconductor count derfinder deseq2 exon gene human illumina junction recount

41 stars 9.57 score 498 scripts 3 dependents

bioc

ggtreeExtra:An R Package To Add Geometric Layers On Circular Or Other Layout Tree Of "ggtree"

'ggtreeExtra' extends the method for mapping and visualizing associated data on phylogenetic tree using 'ggtree'. These associated data can be presented on the external panels to circular layout, fan layout, or other rectangular layout tree built by 'ggtree' with the grammar of 'ggplot2'.

Maintained by Shuangbin Xu. Last updated 5 months ago.

software visualization phylogenetics annotation

91 stars 9.55 score 426 scripts 2 dependents

bioc

scMerge:scMerge: Merging multiple batches of scRNA-seq data

Like all gene expression data, single-cell data suffers from batch effects and other unwanted variations that makes accurate biological interpretations difficult. The scMerge method leverages factor analysis, stably expressed genes (SEGs) and (pseudo-) replicates to remove unwanted variations and merge multiple single-cell data. This package contains all the necessary functions in the scMerge pipeline, including the identification of SEGs, replication-identification methods, and merging of single-cell data.

Maintained by Yingxin Lin. Last updated 5 months ago.

batcheffect geneexpression normalization rnaseq sequencing singlecell software transcriptomics bioinformatics single-cell

67 stars 9.52 score 137 scripts 1 dependents

bioc

InteractiveComplexHeatmap:Make Interactive Complex Heatmaps

This package can easily make heatmaps which are produced by the ComplexHeatmap package into interactive applications. It provides two types of interactivities: 1. on the interactive graphics device, and 2. on a Shiny app. It also provides functions for integrating the interactive heatmap widgets for more complex Shiny app development.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization sequencing interactive-heatmaps

134 stars 9.52 score 128 scripts 4 dependents

bioc

Nebulosa:Single-Cell Data Visualisation Using Kernel Gene-Weighted Density Estimation

This package provides a enhanced visualization of single-cell data based on gene-weighted density estimation. Nebulosa recovers the signal from dropped-out features and allows the inspection of the joint expression from multiple features (e.g. genes). Seurat and SingleCellExperiment objects can be used within Nebulosa.

Maintained by Jose Alquicira-Hernandez. Last updated 5 months ago.

software geneexpression singlecell visualization dimensionreduction single-cell single-cell-analysis single-cell-multiomics single-cell-rna-seq

99 stars 9.52 score 494 scripts

bioc

bluster:Clustering Algorithms for Bioconductor

Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.

Maintained by Aaron Lun. Last updated 5 months ago.

immunooncology software geneexpression transcriptomics singlecell clustering cpp

9.43 score 636 scripts 51 dependents

bioc

ggmsa:Plot Multiple Sequence Alignment using 'ggplot2'

A visual exploration tool for multiple sequence alignment and associated data. Supports MSA of DNA, RNA, and protein sequences using 'ggplot2'. Multiple sequence alignment can easily be combined with other 'ggplot2' plots, such as phylogenetic tree Visualized by 'ggtree', boxplot, genome map and so on. More features: visualization of sequence logos, sequence bundles, RNA secondary structures and detection of sequence recombinations.

Maintained by Guangchuang Yu. Last updated 3 months ago.

software visualization alignment annotation multiplesequencealignment

210 stars 9.35 score 196 scripts 2 dependents

bioc

GenomicInteractions:Utilities for handling genomic interaction data

Utilities for handling genomic interaction data such as ChIA-PET or Hi-C, annotating genomic features with interaction information, and producing plots and summary statistics.

Maintained by Liz Ing-Simmons. Last updated 5 months ago.

software infrastructure dataimport datarepresentation hic

7 stars 9.31 score 162 scripts 5 dependents

bioc

batchelor:Single-Cell Batch Correction Methods

Implements a variety of methods for batch correction of single-cell (RNA sequencing) data. This includes methods based on detecting mutually nearest neighbors, as well as several efficient variants of linear regression of the log-expression values. Functions are also provided to perform global rescaling to remove differences in depth between batches, and to perform a principal components analysis that is robust to differences in the numbers of cells across batches.

Maintained by Aaron Lun. Last updated 16 days ago.

sequencing rnaseq software geneexpression transcriptomics singlecell batcheffect normalization cpp

9.10 score 1.2k scripts 10 dependents

bioc

BatchQC:Batch Effects Quality Control Software

Sequencing and microarray samples often are collected or processed in multiple batches or at different times. This often produces technical biases that can lead to incorrect results in the downstream analysis. BatchQC is a software tool that streamlines batch preprocessing and evaluation by providing interactive diagnostics, visualizations, and statistical analyses to explore the extent to which batch variation impacts the data. BatchQC diagnostics help determine whether batch adjustment needs to be done, and how correction should be applied before proceeding with a downstream analysis. Moreover, BatchQC interactively applies multiple common batch effect approaches to the data and the user can quickly see the benefits of each method. BatchQC is developed as a Shiny App. The output is organized into multiple tabs and each tab features an important part of the batch effect analysis and visualization of the data. The BatchQC interface has the following analysis groups: Summary, Differential Expression, Median Correlations, Heatmaps, Circular Dendrogram, PCA Analysis, Shape, ComBat and SVA.

Maintained by Jessica Anderson. Last updated 11 days ago.

batcheffect graphandnetwork microarray normalization principalcomponent sequencing software visualization qualitycontrol rnaseq preprocessing differentialexpression immunooncology

7 stars 9.06 score 54 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 2 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

203 stars 9.04 score 91 scripts 1 dependents

bioc

scPipe:Pipeline for single cell multi-omic data pre-processing

A preprocessing pipeline for single cell RNA-seq/ATAC-seq data that starts from the fastq files and produces a feature count matrix with associated quality control information. It can process fastq data generated by CEL-seq, MARS-seq, Drop-seq, Chromium 10x and SMART-seq protocols.

Maintained by Shian Su. Last updated 3 months ago.

immunooncology software sequencing rnaseq geneexpression singlecell visualization sequencematching preprocessing qualitycontrol genomeannotation dataimport curl bzip2 xz-utils zlib cpp

68 stars 9.02 score 84 scripts

bioc

scone:Single Cell Overview of Normalized Expression data

SCONE is an R package for comparing and ranking the performance of different normalization schemes for single-cell RNA-seq and other high-throughput analyses.

Maintained by Davide Risso. Last updated 1 months ago.

immunooncology normalization preprocessing qualitycontrol geneexpression rnaseq software transcriptomics sequencing singlecell coverage

53 stars 9.00 score 104 scripts

bioc

schex:Hexbin plots for single cell omics data

Builds hexbin plots for variables and dimension reduction stored in single cell omics data such as SingleCellExperiment. The ideas used in this package are based on the excellent work of Dan Carr, Nicholas Lewin-Koh, Martin Maechler and Thomas Lumley.

Maintained by Saskia Freytag. Last updated 5 months ago.

software sequencing singlecell dimensionreduction visualization immunooncology dataimport

74 stars 8.96 score 102 scripts 2 dependents

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 29 days ago.

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

25 stars 8.94 score 115 scripts

bioc

RTCGA:The Cancer Genome Atlas Data Integration

The Cancer Genome Atlas (TCGA) Data Portal provides a platform for researchers to search, download, and analyze data sets generated by TCGA. It contains clinical information, genomic characterization data, and high level sequence analysis of the tumor genomes. The key is to understand genomics to improve cancer care. RTCGA package offers download and integration of the variety and volume of TCGA data using patient barcode key, what enables easier data possession. This may have an benefcial infuence on impact on development of science and improvement of patients' treatment. Furthermore, RTCGA package transforms TCGA data to tidy form which is convenient to use.

Maintained by Marcin Kosinski. Last updated 5 months ago.

immunooncology software dataimport datarepresentation preprocessing rnaseq survival dnamethylation principalcomponent visualization

51 stars 8.91 score 106 scripts 1 dependents

bioc

scmap:A tool for unsupervised projection of single cell RNA-seq data

Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.

Maintained by Vladimir Kiselev. Last updated 5 months ago.

immunooncology singlecell software classification supportvectormachine rnaseq visualization transcriptomics datarepresentation transcription sequencing preprocessing geneexpression dataimport bioconductor-package human-cell-atlas projection-mapping single-cell-rna-seq openblas cpp

95 stars 8.82 score 172 scripts

bioc

CellBench:Construct Benchmarks for Single Cell Analysis Methods

This package contains infrastructure for benchmarking analysis methods and access to single cell mixture benchmarking data. It provides a framework for organising analysis methods and testing combinations of methods in a pipeline without explicitly laying out each combination. It also provides utilities for sampling and filtering SingleCellExperiment objects, constructing lists of functions with varying parameters, and multithreaded evaluation of analysis methods.

Maintained by Shian Su. Last updated 5 months ago.

software infrastructure singlecell benchmark bioinformatics

31 stars 8.73 score 98 scripts

bioc

qpgraph:Estimation of Genetic and Molecular Regulatory Networks from High-Throughput Genomics Data

Estimate gene and eQTL networks from high-throughput expression and genotyping assays.

Maintained by Robert Castelo. Last updated 18 hours ago.

microarray geneexpression transcription pathways networkinference graphandnetwork generegulation genetics geneticvariability snp software openblas

3 stars 8.72 score 20 scripts 3 dependents

enblacar

SCpubr:Generate Publication Ready Visualizations of Single Cell Transcriptomics Data

A system that provides a streamlined way of generating publication ready plots for known Single-Cell transcriptomics data in a “publication ready” format. This is, the goal is to automatically generate plots with the highest quality possible, that can be used right away or with minimal modifications for a research article.

Maintained by Enrique Blanco-Carmona. Last updated 1 months ago.

software singlecell visualization data-visualization ggplot2 publication-quality-plots seurat single-cell single-cell-genomics single-cell-rna-seq

178 stars 8.71 score 194 scripts

bioc

memes:motif matching, comparison, and de novo discovery using the MEME Suite

A seamless interface to the MEME Suite family of tools for motif analysis. 'memes' provides data aware utilities for using GRanges objects as entrypoints to motif analysis, data structures for examining & editing motif lists, and novel data visualizations. 'memes' functions and data structures are amenable to both base R and tidyverse workflows.

Maintained by Spencer Nystrom. Last updated 5 months ago.

dataimport functionalgenomics generegulation motifannotation motifdiscovery sequencematching software

50 stars 8.69 score 117 scripts 1 dependents

bioc

BiocBaseUtils:General utility functions for developing Bioconductor packages

The package provides utility functions related to package development. These include functions that replace slots, and selectors for show methods. It aims to coalesce the various helper functions often re-used throughout the Bioconductor ecosystem.

Maintained by Marcel Ramos. Last updated 5 months ago.

software infrastructure bioconductor-package core-package

4 stars 8.68 score 3 scripts 159 dependents

bioc

miaViz:Microbiome Analysis Plotting and Visualization

The miaViz package implements functions to visualize TreeSummarizedExperiment objects especially in the context of microbiome analysis. Part of the mia family of R/Bioconductor packages.

Maintained by Tuomas Borman. Last updated 10 days ago.

microbiome software visualization bioconductor microbiome-analysis plotting

10 stars 8.67 score 81 scripts 1 dependents

bioc

HiCcompare:HiCcompare: Joint normalization and comparative analysis of multiple Hi-C datasets

HiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. HiCcompare operates on processed Hi-C data in the form of chromosome-specific chromatin interaction matrices. It accepts three-column tab-separated text files storing chromatin interaction matrices in a sparse matrix format which are available from several sources. HiCcompare is designed to give the user the ability to perform a comparative analysis on the 3-Dimensional structure of the genomes of cells in different biological states.`HiCcompare` differs from other packages that attempt to compare Hi-C data in that it works on processed data in chromatin interaction matrix format instead of pre-processed sequencing data. In addition, `HiCcompare` provides a non-parametric method for the joint normalization and removal of biases between two Hi-C datasets for the purpose of comparative analysis. `HiCcompare` also provides a simple yet robust method for detecting differences between Hi-C datasets.

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing normalization difference-detection hi-c visualization

20 stars 8.63 score 51 scripts 5 dependents

bioc

SPIAT:Spatial Image Analysis of Tissues

SPIAT (**Sp**atial **I**mage **A**nalysis of **T**issues) is an R package with a suite of data processing, quality control, visualization and data analysis tools. SPIAT is compatible with data generated from single-cell spatial proteomics platforms (e.g. OPAL, CODEX, MIBI, cellprofiler). SPIAT reads spatial data in the form of X and Y coordinates of cells, marker intensities and cell phenotypes. SPIAT includes six analysis modules that allow visualization, calculation of cell colocalization, categorization of the immune microenvironment relative to tumor areas, analysis of cellular neighborhoods, and the quantification of spatial heterogeneity, providing a comprehensive toolkit for spatial data analysis.

Maintained by Yuzhou Feng. Last updated 13 days ago.

biomedicalinformatics cellbiology spatial clustering dataimport immunooncology qualitycontrol singlecell software visualization

22 stars 8.59 score 69 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

29 stars 8.53 score 119 scripts 2 dependents

bioc

FRASER:Find RAre Splicing Events in RNA-Seq Data

Detection of rare aberrant splicing events in transcriptome profiles. Read count ratio expectations are modeled by an autoencoder to control for confounding factors in the data. Given these expectations, the ratios are assumed to follow a beta-binomial distribution with a junction specific dispersion. Outlier events are then identified as read-count ratios that deviate significantly from this distribution. FRASER is able to detect alternative splicing, but also intron retention. The package aims to support diagnostics in the field of rare diseases where RNA-seq is performed to identify aberrant splicing defects.

Maintained by Christian Mertes. Last updated 5 months ago.

rnaseq alternativesplicing sequencing software genetics coverage aberrant-splicing diagnostics outlier-detection rare-disease rna-seq splicing openblas cpp

41 stars 8.50 score 155 scripts

bioc

MSstats:Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments

A set of tools for statistical relative protein significance analysis in DDA, SRM and DIA experiments.

Maintained by Meena Choi. Last updated 24 days ago.

immunooncology massspectrometry proteomics software normalization qualitycontrol timecourse openblas cpp

8.49 score 164 scripts 7 dependents

bioc

BgeeDB:Annotation and gene expression data retrieval from Bgee database. TopAnat, an anatomical entities Enrichment Analysis tool for UBERON ontology

A package for the annotation and gene expression data download from Bgee database, and TopAnat analysis: GO-like enrichment of anatomical terms, mapped to genes by expression patterns.

Maintained by Julien Wollbrett. Last updated 5 months ago.

software dataimport sequencing geneexpression microarray go genesetenrichment bioinformatics enrichment-analysis rna-seq scrna-seq single-cell

15 stars 8.46 score 19 scripts 1 dependents

bioc

lefser:R implementation of the LEfSE method for microbiome biomarker discovery

lefser is the R implementation of the popular microbiome biomarker discovery too, LEfSe. It uses the Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis to find biomarkers from two-level classes (and optional sub-classes).

Maintained by Sehyun Oh. Last updated 1 months ago.

software sequencing differentialexpression microbiome statisticalmethod classification bioconductor-package r01ca230551

56 stars 8.44 score 56 scripts

bioc

ScaledMatrix:Creating a DelayedMatrix of Scaled and Centered Values

Provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale() function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.

Maintained by Aaron Lun. Last updated 2 months ago.

software datarepresentation

8.44 score 10 scripts 105 dependents

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 11 days ago.

functionalprediction generegulation biologicalquestion software

62 stars 8.42 score 70 scripts

bioc

ConsensusClusterPlus:ConsensusClusterPlus

algorithm for determining cluster count and membership by stability evidence in unsupervised analysis

Maintained by Matt Wilkerson. Last updated 5 months ago.

software clustering

8.35 score 412 scripts 22 dependents

bioc

rols:An R interface to the Ontology Lookup Service

The rols package is an interface to the Ontology Lookup Service (OLS) to access and query hundred of ontolgies directly from R.

Maintained by Laurent Gatto. Last updated 5 months ago.

immunooncology software annotation massspectrometry go

11 stars 8.30 score 89 scripts 5 dependents

bioc

GeneTonic:Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis

This package provides functionality to combine the existing pieces of the transcriptome data and results, making it easier to generate insightful observations and hypothesis. Its usage is made easy with a Shiny application, combining the benefits of interactivity and reproducibility e.g. by capturing the features and gene sets of interest highlighted during the live session, and creating an HTML report as an artifact where text, code, and output coexist. Using the GeneTonicList as a standardized container for all the required components, it is possible to simplify the generation of multiple visualizations and summaries.

Maintained by Federico Marini. Last updated 3 months ago.

gui geneexpression software transcription transcriptomics visualization differentialexpression pathways reportwriting genesetenrichment annotation go shinyapps bioconductor bioconductor-package data-exploration data-visualization functional-enrichment-analysis gene-expression pathway-analysis reproducible-research rna-seq-analysis rna-seq-data shiny transcriptome user-friendly

77 stars 8.28 score 37 scripts 1 dependents

bioc

gtrellis:Genome Level Trellis Layout

Genome level Trellis graph visualizes genomic data conditioned by genomic categories (e.g. chromosomes). For each genomic category, multiple dimensional data which are represented as tracks describe different features from different aspects. This package provides high flexibility to arrange genomic categories and to add self-defined graphics in the plot.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization sequencing

39 stars 8.24 score 37 scripts 1 dependents

bioc

rawrr:Direct Access to Orbitrap Data and Beyond

This package wraps the functionality of the Thermo Fisher Scientic RawFileReader .NET 8.0 assembly. Within the R environment, spectra and chromatograms are represented by S3 objects. The package provides basic functions to download and install the required third-party libraries. The package is developed, tested, and used at the Functional Genomics Center Zurich, Switzerland.

Maintained by Christian Panse. Last updated 4 months ago.

massspectrometry proteomics metabolomics infrastructure software fast mass-spectrometry multiplatform orbitrap-ms

56 stars 8.19 score 23 scripts 2 dependents

bioc

POMA:Tools for Omics Data Analysis

The POMA package offers a comprehensive toolkit designed for omics data analysis, streamlining the process from initial visualization to final statistical analysis. Its primary goal is to simplify and unify the various steps involved in omics data processing, making it more accessible and manageable within a single, intuitive R package. Emphasizing on reproducibility and user-friendliness, POMA leverages the standardized SummarizedExperiment class from Bioconductor, ensuring seamless integration and compatibility with a wide array of Bioconductor tools. This approach guarantees maximum flexibility and replicability, making POMA an essential asset for researchers handling omics datasets. See https://github.com/pcastellanoescuder/POMAShiny. Paper: Castellano-Escuder et al. (2021) <doi:10.1371/journal.pcbi.1009148> for more details.

Maintained by Pol Castellano-Escuder. Last updated 4 months ago.

batcheffect classification clustering decisiontree dimensionreduction multidimensionalscaling normalization preprocessing principalcomponent regression rnaseq software statisticalmethod visualization bioconductor bioinformatics data-visualization dimension-reduction exploratory-data-analysis machine-learning omics-data-integration pipeline pre-processing statistical-analysis user-friendly workflow

11 stars 8.16 score 20 scripts 1 dependents

bioc

maaslin3:"Refining and extending generalized multivariate linear models for meta-omic association discovery"

MaAsLin 3 refines and extends generalized multivariate linear models for meta-omicron association discovery. It finds abundance and prevalence associations between microbiome meta-omics features and complex metadata in population-scale epidemiological studies. The software includes multiple analysis methods (including support for multiple covariates, repeated measures, and ordered predictors), filtering, normalization, and transform options to customize analysis for your specific study.

Maintained by William Nickols. Last updated 4 days ago.

metagenomics software microbiome normalization multiplecomparison

33 stars 8.16 score 34 scripts

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 4 days ago.

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

12 stars 8.14 score 128 scripts

gfellerlab

SuperCell:Simplification of scRNA-seq data by merging together similar cells

Aggregates large single-cell data into metacell dataset by merging together gene expression of very similar cells.

Maintained by The package maintainer. Last updated 8 months ago.

software coarse-graining scrna-seq-analysis scrna-seq-data

72 stars 8.08 score 93 scripts

bioc

MSstatsPTM:Statistical Characterization of Post-translational Modifications

MSstatsPTM provides general statistical methods for quantitative characterization of post-translational modifications (PTMs). Supports DDA, DIA, SRM, and tandem mass tag (TMT) labeling. Typically, the analysis involves the quantification of PTM sites (i.e., modified residues) and their corresponding proteins, as well as the integration of the quantification results. MSstatsPTM provides functions for summarization, estimation of PTM site abundance, and detection of changes in PTMs across experimental conditions.

Maintained by Devon Kohler. Last updated 4 months ago.

immunooncology massspectrometry proteomics software differentialexpression onechannel twochannel normalization qualitycontrol post-translational-modification cpp

10 stars 8.03 score 36 scripts 2 dependents

bioc

recount3:Explore and download data from the recount3 project

The recount3 package enables access to a large amount of uniformly processed RNA-seq data from human and mouse. You can download RangedSummarizedExperiment objects at the gene, exon or exon-exon junctions level with sample metadata and QC statistics. In addition we provide access to sample coverage BigWig files.

Maintained by Leonardo Collado-Torres. Last updated 4 months ago.

coverage differentialexpression geneexpression rnaseq sequencing software dataimport annotation-agnostic bioconductor count derfinder exon gene human illumina junction mouse recount recount3

33 stars 8.03 score 216 scripts

bioc

simplifyEnrichment:Simplify Functional Enrichment Results

A new clustering algorithm, "binary cut", for clustering similarity matrices of functional terms is implemeted in this package. It also provides functions for visualizing, summarizing and comparing the clusterings.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization go clustering genesetenrichment

113 stars 8.02 score 196 scripts

bioc

philr:Phylogenetic partitioning based ILR transform for metagenomics data

PhILR is short for Phylogenetic Isometric Log-Ratio Transform. This package provides functions for the analysis of compositional data (e.g., data representing proportions of different variables/parts). Specifically this package allows analysis of compositional data where the parts can be related through a phylogenetic tree (as is common in microbiota survey data) and makes available the Isometric Log Ratio transform built from the phylogenetic tree and utilizing a weighted reference measure.

Maintained by Justin Silverman. Last updated 5 months ago.

immunooncology sequencing microbiome metagenomics software

19 stars 7.99 score 95 scripts

bioc

InteractionSet:Base Classes for Storing Genomic Interaction Data

Provides the GInteractions, InteractionSet and ContactMatrix objects and associated methods for storing and manipulating genomic interaction data from Hi-C and ChIA-PET experiments.

Maintained by Aaron Lun. Last updated 5 months ago.

infrastructure datarepresentation software hic cpp

7.95 score 250 scripts 36 dependents

bioc

AneuFinder:Analysis of Copy Number Variation in Single-Cell-Sequencing Data

AneuFinder implements functions for copy-number detection, breakpoint detection, and karyotype and heterogeneity analysis in single-cell whole genome sequencing and strand-seq data.

Maintained by Aaron Taudt. Last updated 3 days ago.

immunooncology software sequencing singlecell copynumbervariation genomicvariation hiddenmarkovmodel wholegenome cpp

18 stars 7.90 score 37 scripts

bioc

biocthis:Automate package and project setup for Bioconductor packages

This package expands the usethis package with the goal of helping automate the process of creating R packages for Bioconductor or making them Bioconductor-friendly.

Maintained by Leonardo Collado-Torres. Last updated 8 days ago.

software reportwriting actions bioconductor biocthis github styler usethis

51 stars 7.90 score 4 scripts 1 dependents

bioc

BayesSpace:Clustering and Resolution Enhancement of Spatial Transcriptomes

Tools for clustering and enhancing the resolution of spatial gene expression experiments. BayesSpace clusters a low-dimensional representation of the gene expression matrix, incorporating a spatial prior to encourage neighboring spots to cluster together. The method can enhance the resolution of the low-dimensional representation into "sub-spots", for which features such as gene expression or cell type composition can be imputed.

Maintained by Matt Stone. Last updated 5 months ago.

software clustering transcriptomics geneexpression singlecell immunooncology dataimport openblas cpp openmp

126 stars 7.90 score 278 scripts 1 dependents

bioc

mistyR:Multiview Intercellular SpaTial modeling framework

mistyR is an implementation of the Multiview Intercellular SpaTialmodeling framework (MISTy). MISTy is an explainable machine learning framework for knowledge extraction and analysis of single-cell, highly multiplexed, spatially resolved data. MISTy facilitates an in-depth understanding of marker interactions by profiling the intra- and intercellular relationships. MISTy is a flexible framework able to process a custom number of views. Each of these views can describe a different spatial context, i.e., define a relationship among the observed expressions of the markers, such as intracellular regulation or paracrine regulation, but also, the views can also capture cell-type specific relationships, capture relations between functional footprints or focus on relations between different anatomical regions. Each MISTy view is considered as a potential source of variability in the measured marker expressions. Each MISTy view is then analyzed for its contribution to the total expression of each marker and is explained in terms of the interactions with other measurements that led to the observed contribution.

Maintained by Jovan Tanevski. Last updated 5 months ago.

software biomedicalinformatics cellbiology systemsbiology regression decisiontree singlecell spatial bioconductor biology intercellular machine-learning modular molecular-biology multiview spatial-transcriptomics

51 stars 7.87 score 160 scripts

bioc

biodb:biodb, a library and a development framework for connecting to chemical and biological databases

The biodb package provides access to standard remote chemical and biological databases (ChEBI, KEGG, HMDB, ...), as well as to in-house local database files (CSV, SQLite), with easy retrieval of entries, access to web services, search of compounds by mass and/or name, and mass spectra matching for LCMS and MSMS. Its architecture as a development framework facilitates the development of new database connectors for local projects or inside separate published packages.

Maintained by Pierrick Roger. Last updated 5 months ago.

software infrastructure dataimport kegg biology cheminformatics chemistry databases cpp

11 stars 7.85 score 24 scripts 6 dependents

bioc

Rcpi:Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery

A molecular informatics toolkit with an integration of bioinformatics and chemoinformatics tools for drug discovery.

Maintained by Nan Xiao. Last updated 5 months ago.

software dataimport datarepresentation featureextraction cheminformatics biomedicalinformatics proteomics go systemsbiology bioconductor bioinformatics drug-discovery feature-extraction fingerprint molecular-descriptors protein-sequences

37 stars 7.81 score 29 scripts

bioc

PhyloProfile:PhyloProfile

PhyloProfile is a tool for exploring complex phylogenetic profiles. Phylogenetic profiles, presence/absence patterns of genes over a set of species, are commonly used to trace the functional and evolutionary history of genes across species and time. With PhyloProfile we can enrich regular phylogenetic profiles with further data like sequence/structure similarity, to make phylogenetic profiling more meaningful. Besides the interactive visualisation powered by R-Shiny, the package offers a set of further analysis features to gain insights like the gene age estimation or core gene identification.

Maintained by Vinh Tran. Last updated 8 days ago.

software visualization datarepresentation multiplecomparison functionalprediction dimensionreduction bioinformatics heatmap interactive-visualizations orthologs phylogenetic-profile shiny

33 stars 7.79 score 10 scripts

bioc

target:Predict Combined Function of Transcription Factors

Implement the BETA algorithm for infering direct target genes from DNA-binding and perturbation expression data Wang et al. (2013) <doi: 10.1038/nprot.2013.150>. Extend the algorithm to predict the combined function of two DNA-binding elements from comprable binding and expression data.

Maintained by Mahmoud Ahmed. Last updated 5 months ago.

software statisticalmethod transcription algorithm chip-seq dna-binding gene-regulation transcription-factors

4 stars 7.79 score 1.3k scripts

bioc

scDiagnostics:Cell type annotation diagnostics

The scDiagnostics package provides diagnostic plots to assess the quality of cell type assignments from single cell gene expression profiles. The implemented functionality allows to assess the reliability of cell type annotations, investigate gene expression patterns, and explore relationships between different cell types in query and reference datasets allowing users to detect potential misalignments between reference and query datasets. The package also provides visualization capabilities for diagnostics purposes.

Maintained by Anthony Christidis. Last updated 5 months ago.

annotation classification clustering geneexpression rnaseq singlecell software transcriptomics

8 stars 7.77 score 46 scripts

bioc

rrvgo:Reduce + Visualize GO

Reduce and visualize lists of Gene Ontology terms by identifying redudance based on semantic similarity.

Maintained by Sergi Sayols. Last updated 5 months ago.

annotation clustering go network pathways software

24 stars 7.74 score 190 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

20 stars 7.71 score 48 scripts 1 dependents

bioc

FlowSOM:Using self-organizing maps for visualization and interpretation of cytometry data

FlowSOM offers visualization options for cytometry data, by using Self-Organizing Map clustering and Minimal Spanning Trees.

Maintained by Sofie Van Gassen. Last updated 5 months ago.

cellbiology flowcytometry clustering visualization software cellbasedassays

7.71 score 468 scripts 10 dependents

bioc

BioNERO:Biological Network Reconstruction Omnibus

BioNERO aims to integrate all aspects of biological network inference in a single package, including data preprocessing, exploratory analyses, network inference, and analyses for biological interpretations. BioNERO can be used to infer gene coexpression networks (GCNs) and gene regulatory networks (GRNs) from gene expression data. Additionally, it can be used to explore topological properties of protein-protein interaction (PPI) networks. GCN inference relies on the popular WGCNA algorithm. GRN inference is based on the "wisdom of the crowds" principle, which consists in inferring GRNs with multiple algorithms (here, CLR, GENIE3 and ARACNE) and calculating the average rank for each interaction pair. As all steps of network analyses are included in this package, BioNERO makes users avoid having to learn the syntaxes of several packages and how to communicate between them. Finally, users can also identify consensus modules across independent expression sets and calculate intra and interspecies module preservation statistics between different networks.

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

software geneexpression generegulation systemsbiology graphandnetwork preprocessing network networkinference

27 stars 7.69 score 50 scripts 1 dependents

bioc

BiocPkgTools:Collection of simple tools for learning about Bioconductor Packages

Bioconductor has a rich ecosystem of metadata around packages, usage, and build status. This package is a simple collection of functions to access that metadata from R. The goal is to expose metadata for data mining and value-added functionality such as package searching, text mining, and analytics on packages.

Maintained by Sean Davis. Last updated 25 days ago.

software infrastructure bioconductor metadata

21 stars 7.67 score 68 scripts

neurogenomics

rworkflows:Test, Document, Containerise, and Deploy R Packages

Reproducibility is essential to the progress of research, yet achieving it remains elusive even in computational fields. Continuous Integration (CI) platforms offer a powerful way to launch automated workflows to check and document code, but often require considerable time, effort, and technical expertise to setup. We therefore developed the rworkflows suite to make robust CI workflows easy and freely accessible to all R package developers. rworkflows consists of 1) a CRAN/Bioconductor-compatible R package template, 2) an R package to quickly implement a standardised workflow, and 3) a centrally maintained GitHub Action.

Maintained by Brian Schilder. Last updated 2 months ago.

software workflowmanagement bioconductor containers continuous-integration docker dockerhub github-actions reproducibility workflows

79 stars 7.60 score 6 scripts

bioc

scDesign3:A unified framework of realistic in silico data generation and statistical model inference for single-cell and spatial omics

We present a statistical simulator, scDesign3, to generate realistic single-cell and spatial omics data, including various cell states, experimental designs, and feature modalities, by learning interpretable parameters from real data. Using a unified probabilistic model for single-cell and spatial omics data, scDesign3 infers biologically meaningful parameters; assesses the goodness-of-fit of inferred cell clusters, trajectories, and spatial locations; and generates in silico negative and positive controls for benchmarking computational tools.

Maintained by Dongyuan Song. Last updated 27 days ago.

software singlecell sequencing geneexpression spatial

89 stars 7.59 score 25 scripts

bioc

AlpsNMR:Automated spectraL Processing System for NMR

Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.

Maintained by Sergio Oller Moreno. Last updated 5 months ago.

software preprocessing visualization classification cheminformatics metabolomics dataimport

15 stars 7.59 score 12 scripts 1 dependents

bioc

ggsc:Visualizing Single Cell and Spatial Transcriptomics

Useful functions to visualize single cell and spatial data. It supports visualizing 'Seurat', 'SingleCellExperiment' and 'SpatialExperiment' objects through grammar of graphics syntax implemented in 'ggplot2'.

Maintained by Guangchuang Yu. Last updated 5 months ago.

dimensionreduction geneexpression singlecell software spatial transcriptomics visualization openblas cpp openmp

47 stars 7.59 score 18 scripts

bioc

dittoSeq:User Friendly Single-Cell and Bulk RNA Sequencing Visualization

A universal, user friendly, single-cell and bulk RNA sequencing visualization toolkit that allows highly customizable creation of color blindness friendly, publication-quality figures. dittoSeq accepts both SingleCellExperiment (SCE) and Seurat objects, as well as the import and usage, via conversion to an SCE, of SummarizedExperiment or DGEList bulk data. Visualizations include dimensionality reduction plots, heatmaps, scatterplots, percent composition or expression across groups, and more. Customizations range from size and title adjustments to automatic generation of annotations for heatmaps, overlay of trajectory analysis onto any dimensionality reduciton plot, hidden data overlay upon cursor hovering via ggplotly conversion, and many more. All with simple, discrete inputs. Color blindness friendliness is powered by legend adjustments (enlarged keys), and by allowing the use of shapes or letter-overlay in addition to the carefully selected dittoColors().

Maintained by Daniel Bunis. Last updated 5 months ago.

software visualization rnaseq singlecell geneexpression transcriptomics dataimport

7.56 score 760 scripts 2 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

173 stars 7.53 score 141 scripts

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

19 stars 7.52 score 48 scripts 1 dependents

bioc

SimBu:Simulate Bulk RNA-seq Datasets from Single-Cell Datasets

SimBu can be used to simulate bulk RNA-seq datasets with known cell type fractions. You can either use your own single-cell study for the simulation or the sfaira database. Different pre-defined simulation scenarios exist, as are options to run custom simulations. Additionally, expression values can be adapted by adding an mRNA bias, which produces more biologically relevant simulations.

Maintained by Alexander Dietrich. Last updated 1 days ago.

software rnaseq singlecell

15 stars 7.50 score 29 scripts 1 dependents

bioc

koinar:KoinaR - Remote machine learning inference using Koina

A client to simplify fetching predictions from the Koina web service. Koina is a model repository enabling the remote execution of models. Predictions are generated as a response to HTTP/S requests, the standard protocol used for nearly all web traffic.

Maintained by Ludwig Lautenbacher. Last updated 3 months ago.

massspectrometry proteomics infrastructure software bioinformatics deep-learning machine-learning mass-spectrometry python

34 stars 7.49 score 4 scripts

bioc

cola:A Framework for Consensus Partitioning

Subgroup classification is a basic task in genomic data analysis, especially for gene expression and DNA methylation data analysis. It can also be used to test the agreement to known clinical annotations, or to test whether there exist significant batch effects. The cola package provides a general framework for subgroup classification by consensus partitioning. It has the following features: 1. It modularizes the consensus partitioning processes that various methods can be easily integrated. 2. It provides rich visualizations for interpreting the results. 3. It allows running multiple methods at the same time and provides functionalities to straightforward compare results. 4. It provides a new method to extract features which are more efficient to separate subgroups. 5. It automatically generates detailed reports for the complete analysis. 6. It allows applying consensus partitioning in a hierarchical manner.

Maintained by Zuguang Gu. Last updated 2 months ago.

clustering geneexpression classification software consensus-clustering cpp

61 stars 7.49 score 112 scripts

bioc

CAGEfightR:Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor

CAGE is a widely used high throughput assay for measuring transcription start site (TSS) activity. CAGEfightR is an R/Bioconductor package for performing a wide range of common data analysis tasks for CAGE and 5'-end data in general. Core functionality includes: import of CAGE TSSs (CTSSs), tag (or unidirectional) clustering for TSS identification, bidirectional clustering for enhancer identification, annotation with transcript and gene models, correlation of TSS and enhancer expression, calculation of TSS shapes, quantification of CAGE expression as expression matrices and genome brower visualization.

Maintained by Malte Thodberg. Last updated 5 months ago.

software transcription coverage geneexpression generegulation peakdetection dataimport datarepresentation transcriptomics sequencing annotation genomebrowsers normalization preprocessing visualization

8 stars 7.46 score 67 scripts 1 dependents

bioc

HilbertCurve:Making 2D Hilbert Curve

Hilbert curve is a type of space-filling curves that fold one dimensional axis into a two dimensional space, but with still preserves the locality. This package aims to provide an easy and flexible way to visualize data through Hilbert curve.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization sequencing coverage genomeannotation cpp

42 stars 7.45 score 48 scripts

bioc

GenomicDistributions:GenomicDistributions: fast analysis of genomic intervals with Bioconductor

If you have a set of genomic ranges, this package can help you with visualization and comparison. It produces several kinds of plots, for example: Chromosome distribution plots, which visualize how your regions are distributed over chromosomes; feature distance distribution plots, which visualizes how your regions are distributed relative to a feature of interest, like Transcription Start Sites (TSSs); genomic partition plots, which visualize how your regions overlap given genomic features such as promoters, introns, exons, or intergenic regions. It also makes it easy to compare one set of ranges to another.

Maintained by Kristyna Kupkova. Last updated 5 months ago.

software genomeannotation genomeassembly datarepresentation sequencing coverage functionalgenomics visualization

26 stars 7.44 score 25 scripts

bioc

glmSparseNet:Network Centrality Metrics for Elastic-Net Regularized Models

glmSparseNet is an R-package that generalizes sparse regression models when the features (e.g. genes) have a graph structure (e.g. protein-protein interactions), by including network-based regularizers. glmSparseNet uses the glmnet R-package, by including centrality measures of the network as penalty weights in the regularization. The current version implements regularization based on node degree, i.e. the strength and/or number of its associated edges, either by promoting hubs in the solution or orphan genes in the solution. All the glmnet distribution families are supported, namely "gaussian", "poisson", "binomial", "multinomial", "cox", and "mgaussian".

Maintained by André Veríssimo. Last updated 5 months ago.

software statisticalmethod dimensionreduction regression classification survival network graphandnetwork

6 stars 7.42 score 41 scripts 1 dependents

bioc

HPAanalyze:Retrieve and analyze data from the Human Protein Atlas

Provide functions for retrieving, exploratory analyzing and visualizing the Human Protein Atlas data.

Maintained by Anh Nhat Tran. Last updated 5 months ago.

proteomics cellbiology visualization software

34 stars 7.42 score 37 scripts

bioc

ELMER:Inferring Regulatory Element Landscapes and Transcription Factor Networks Using Cancer Methylomes

ELMER is designed to use DNA methylation and gene expression from a large number of samples to infere regulatory element landscape and transcription factor network in primary tissue.

Maintained by Tiago Chedraoui Silva. Last updated 5 months ago.

dnamethylation geneexpression motifannotation software generegulation transcription network

7.42 score 176 scripts

bioc

MOSim:Multi-Omics Simulation (MOSim)

MOSim package simulates multi-omic experiments that mimic regulatory mechanisms within the cell, allowing flexible experimental design including time course and multiple groups.

Maintained by Sonia Tarazona. Last updated 5 months ago.

software timecourse experimentaldesign rnaseq cpp

9 stars 7.42 score 11 scripts

bioc

gDRutils:A package with helper functions for processing drug response data

This package contains utility functions used throughout the gDR platform to fit data, manipulate data, and convert and validate data structures. This package also has the necessary default constants for gDR platform. Many of the functions are utilized by the gDRcore package.

Maintained by Arkadiusz Gladki. Last updated 1 days ago.

software infrastructure

2 stars 7.42 score 3 scripts 3 dependents

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

31 stars 7.42 score 28 scripts

bioc

mbkmeans:Mini-batch K-means Clustering for Single-Cell RNA-seq

Implements the mini-batch k-means algorithm for large datasets, including support for on-disk data representation.

Maintained by Davide Risso. Last updated 5 months ago.

clustering geneexpression rnaseq software transcriptomics sequencing singlecell human-cell-atlas cpp

10 stars 7.41 score 54 scripts 2 dependents

bioc

sevenbridges:Seven Bridges Platform API Client and Common Workflow Language Tool Builder in R

R client and utilities for Seven Bridges platform API, from Cancer Genomics Cloud to other Seven Bridges supported platforms.

Maintained by Phil Webster. Last updated 5 months ago.

software dataimport thirdpartyclient api-client bioconductor bioinformatics cloud common-workflow-language sevenbridges

35 stars 7.40 score 24 scripts

bioc

igvShiny:igvShiny: a wrapper of Integrative Genomics Viewer (IGV - an interactive tool for visualization and exploration integrated genomic data)

This package is a wrapper of Integrative Genomics Viewer (IGV). It comprises an htmlwidget version of IGV. It can be used as a module in Shiny apps.

Maintained by Arkadiusz Gladki. Last updated 5 months ago.

software shinyapps sequencing coverage

37 stars 7.40 score 120 scripts

bioc

ASSIGN:Adaptive Signature Selection and InteGratioN (ASSIGN)

ASSIGN is a computational tool to evaluate the pathway deregulation/activation status in individual patient samples. ASSIGN employs a flexible Bayesian factor analysis approach that adapts predetermined pathway signatures derived either from knowledge-based literature or from perturbation experiments to the cell-/tissue-specific pathway signatures. The deregulation/activation level of each context-specific pathway is quantified to a score, which represents the extent to which a patient sample encompasses the pathway deregulation/activation signature.

Maintained by Ying Shen. Last updated 5 months ago.

software geneexpression pathways bayesian

2 stars 7.37 score 65 scripts 1 dependents

eltebioinformatics

mulea:Enrichment Analysis Using Multiple Ontologies and False Discovery Rate

Background - Traditional gene set enrichment analyses are typically limited to a few ontologies and do not account for the interdependence of gene sets or terms, resulting in overcorrected p-values. To address these challenges, we introduce mulea, an R package offering comprehensive overrepresentation and functional enrichment analysis. Results - mulea employs a progressive empirical false discovery rate (eFDR) method, specifically designed for interconnected biological data, to accurately identify significant terms within diverse ontologies. mulea expands beyond traditional tools by incorporating a wide range of ontologies, encompassing Gene Ontology, pathways, regulatory elements, genomic locations, and protein domains. This flexibility enables researchers to tailor enrichment analysis to their specific questions, such as identifying enriched transcriptional regulators in gene expression data or overrepresented protein domains in protein sets. To facilitate seamless analysis, mulea provides gene sets (in standardised GMT format) for 27 model organisms, covering 22 ontology types from 16 databases and various identifiers resulting in almost 900 files. Additionally, the muleaData ExperimentData Bioconductor package simplifies access to these pre-defined ontologies. Finally, mulea's architecture allows for easy integration of user-defined ontologies, or GMT files from external sources (e.g., MSigDB or Enrichr), expanding its applicability across diverse research areas. Conclusions - mulea is distributed as a CRAN R package. It offers researchers a powerful and flexible toolkit for functional enrichment analysis, addressing limitations of traditional tools with its progressive eFDR and by supporting a variety of ontologies. Overall, mulea fosters the exploration of diverse biological questions across various model organisms.

Maintained by Tamas Stirling. Last updated 4 months ago.

annotation differentialexpression geneexpression genesetenrichment go graphandnetwork multiplecomparison pathways reactome software transcription visualization enrichment enrichment-analysis functional-enrichment-analysis gene-set-enrichment ontologies transcriptomics cpp

28 stars 7.36 score 34 scripts

bioc

scry:Small-Count Analysis Methods for High-Dimensional Data

Many modern biological datasets consist of small counts that are not well fit by standard linear-Gaussian methods such as principal component analysis. This package provides implementations of count-based feature selection and dimension reduction algorithms. These methods can be used to facilitate unsupervised analysis of any high-dimensional data such as single-cell RNA-seq.

Maintained by Kelly Street. Last updated 5 months ago.

dimensionreduction geneexpression normalization principalcomponent rnaseq software sequencing singlecell transcriptomics

19 stars 7.34 score 116 scripts

bioc

gDRimport:Package for handling the import of dose-response data

The package is a part of the gDR suite. It helps to prepare raw drug response data for downstream processing. It mainly contains helper functions for importing/loading/validating dose-response data provided in different file formats.

Maintained by Arkadiusz Gladki. Last updated 2 days ago.

software infrastructure dataimport

3 stars 7.32 score 5 scripts 1 dependents

bioc

Wrench:Wrench normalization for sparse count data

Wrench is a package for normalization sparse genomic count data, like that arising from 16s metagenomic surveys.

Maintained by Hector Corrada Bravo. Last updated 5 months ago.

normalization sequencing software

6 stars 7.30 score 10 scripts 8 dependents

bioc

multiHiCcompare:Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available

multiHiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing normalization

9 stars 7.30 score 37 scripts 2 dependents

bioc

gDRcore:Processing functions and interface to process and analyze drug dose-response data

This package contains core functions to process and analyze drug response data. The package provides tools for normalizing, averaging, and calculation of gDR metrics data. All core functions are wrapped into the pipeline function allowing analyzing the data in a straightforward way.

Maintained by Arkadiusz Gladki. Last updated 17 days ago.

software shinyapps cpp

2 stars 7.25 score 4 scripts 1 dependents

bioc

regionReport:Generate HTML or PDF reports for a set of genomic regions or DESeq2/edgeR results

Generate HTML or PDF reports to explore a set of regions such as the results from annotation-agnostic expression analysis of RNA-seq data at base-pair resolution performed by derfinder. You can also create reports for DESeq2 or edgeR results.

Maintained by Leonardo Collado-Torres. Last updated 2 months ago.

differentialexpression sequencing rnaseq software visualization transcription coverage reportwriting differentialmethylation differentialpeakcalling immunooncology qualitycontrol bioconductor derfinder deseq2 edger regionreport rmarkdown

9 stars 7.22 score 46 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.

software

18 stars 7.21 score 50 scripts 1 dependents

bioc

meshes:MeSH Enrichment and Semantic analyses

MeSH (Medical Subject Headings) is the NLM controlled vocabulary used to manually index articles for MEDLINE/PubMed. MeSH terms were associated by Entrez Gene ID by three methods, gendoo, gene2pubmed and RBBH. This association is fundamental for enrichment and semantic analyses. meshes supports enrichment analysis (over-representation and gene set enrichment analysis) of gene list or whole expression profile. The semantic comparisons of MeSH terms provide quantitative ways to compute similarities between genes and gene groups. meshes implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively and supports more than 70 species.

Maintained by Guangchuang Yu. Last updated 5 months ago.

annotation clustering multiplecomparison software enrichment-analysis medical-subject-headings semantic-similarity

12 stars 7.19 score 43 scripts

bioc

signatureSearch:Environment for Gene Expression Searching Combined with Functional Enrichment Analysis

This package implements algorithms and data structures for performing gene expression signature (GES) searches, and subsequently interpreting the results functionally with specialized enrichment methods.

Maintained by Brendan Gongol. Last updated 5 months ago.

software geneexpression go kegg networkenrichment sequencing coverage differentialexpression cpp

17 stars 7.18 score 74 scripts 1 dependents

bioc

CaDrA:Candidate Driver Analysis

Performs both stepwise and backward heuristic search for candidate (epi)genetic drivers based on a binary multi-omics dataset. CaDrA's main objective is to identify features which, together, are significantly skewed or enriched pertaining to a given vector of continuous scores (e.g. sample-specific scores representing a phenotypic readout of interest, such as protein expression, pathway activity, etc.), based on the union occurence (i.e. logical OR) of the events.

Maintained by Reina Chau. Last updated 5 months ago.

microarray rnaseq geneexpression software featureextraction

24 stars 7.11 score 12 scripts

bioc

RiboCrypt:Interactive visualization in genomics

R Package for interactive visualization and browsing NGS data. It contains a browser for both transcript and genomic coordinate view. In addition a QC and general metaplots are included, among others differential translation plots and gene expression plots. The package is still under development.

Maintained by Michal Swirski. Last updated 22 hours ago.

software sequencing riboseq rnaseq

5 stars 7.08 score 22 scripts

bioc

cardelino:Clone Identification from Single Cell Data

Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.

Maintained by Davis McCarthy. Last updated 5 months ago.

singlecell rnaseq visualization transcriptomics geneexpression sequencing software exomeseq clonal-clustering gibbs-sampling scrna-seq single-cell somatic-mutations

61 stars 7.05 score 62 scripts

bioc

msPurity:Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics

msPurity R package was developed to: 1) Assess the spectral quality of fragmentation spectra by evaluating the "precursor ion purity". 2) Process fragmentation spectra. 3) Perform spectral matching. What is precursor ion purity? -What we call "Precursor ion purity" is a measure of the contribution of a selected precursor peak in an isolation window used for fragmentation. The simple calculation involves dividing the intensity of the selected precursor peak by the total intensity of the isolation window. When assessing MS/MS spectra this calculation is done before and after the MS/MS scan of interest and the purity is interpolated at the recorded time of the MS/MS acquisition. Additionally, isotopic peaks can be removed, low abundance peaks are removed that are thought to have limited contribution to the resulting MS/MS spectra and the isolation efficiency of the mass spectrometer can be used to normalise the intensities used for the calculation.

Maintained by Thomas N. Lawson. Last updated 5 months ago.

massspectrometry metabolomics software bioconductor-package dims fragmentation lc-ms lc-msms mass-spectrometry precursor-ion-purity

15 stars 7.03 score 44 scripts

bioc

dir.expiry:Managing Expiration for Cache Directories

Implements an expiration system for access to versioned directories. Directories that have not been accessed by a registered function within a certain time frame are deleted. This aims to reduce disk usage by eliminating obsolete caches generated by old versions of packages.

Maintained by Aaron Lun. Last updated 5 months ago.

software infrastructure

7.03 score 6 scripts 46 dependents

bioc

musicatk:Mutational Signature Comprehensive Analysis Toolkit

Mutational signatures are carcinogenic exposures or aberrant cellular processes that can cause alterations to the genome. We created musicatk (MUtational SIgnature Comprehensive Analysis ToolKit) to address shortcomings in versatility and ease of use in other pre-existing computational tools. Although many different types of mutational data have been generated, current software packages do not have a flexible framework to allow users to mix and match different types of mutations in the mutational signature inference process. Musicatk enables users to count and combine multiple mutation types, including SBS, DBS, and indels. Musicatk calculates replication strand, transcription strand and combinations of these features along with discovery from unique and proprietary genomic feature associated with any mutation type. Musicatk also implements several methods for discovery of new signatures as well as methods to infer exposure given an existing set of signatures. Musicatk provides functions for visualization and downstream exploratory analysis including the ability to compare signatures between cohorts and find matching signatures in COSMIC V2 or COSMIC V3.

Maintained by Joshua D. Campbell. Last updated 5 months ago.

software biologicalquestion somaticmutation variantannotation

13 stars 6.97 score 20 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

21 stars 6.97 score 74 scripts 1 dependents

bioc

BridgeDbR:Code for using BridgeDb identifier mapping framework from within R

Use BridgeDb functions and load identifier mapping databases in R. It uses GitHub, Zenodo, and Figshare if you use this package to download identifier mappings files.

Maintained by Egon Willighagen. Last updated 5 months ago.

software annotation metabolomics cheminformatics bioconductor-package bridgedb genes identifiers life-sciences metabolites proteins openjdk

4 stars 6.97 score 43 scripts

bioc

NanoMethViz:Visualise methylation data from Oxford Nanopore sequencing

NanoMethViz is a toolkit for visualising methylation data from Oxford Nanopore sequencing. It can be used to explore methylation patterns from reads derived from Oxford Nanopore direct DNA sequencing with methylation called by callers including nanopolish, f5c and megalodon. The plots in this package allow the visualisation of methylation profiles aggregated over experimental groups and across classes of genomic features.

Maintained by Shian Su. Last updated 19 days ago.

software longread visualization differentialmethylation dnamethylation epigenetics dataimport zlib cpp

26 stars 6.95 score 11 scripts

bioc

msqrob2:Robust statistical inference for quantitative LC-MS proteomics

msqrob2 provides a robust linear mixed model framework for assessing differential abundance in MS-based Quantitative proteomics experiments. Our workflows can start from raw peptide intensities or summarised protein expression values. The model parameter estimates can be stabilized by ridge regression, empirical Bayes variance estimation and robust M-estimation. msqrob2's hurde workflow can handle missing data without having to rely on hard-to-verify imputation assumptions, and, outcompetes state-of-the-art methods with and without imputation for both high and low missingness. It builds on QFeature infrastructure for quantitative mass spectrometry data to store the model results together with the raw data and preprocessed data.

Maintained by Lieven Clement. Last updated 1 months ago.

proteomics massspectrometry differentialexpression multiplecomparison regression experimentaldesign software immunooncology normalization timecourse preprocessing

10 stars 6.94 score 83 scripts

bioc

TileDBArray:Using TileDB as a DelayedArray Backend

Implements a DelayedArray backend for reading and writing dense or sparse arrays in the TileDB format. The resulting TileDBArrays are compatible with all Bioconductor pipelines that can accept DelayedArray instances.

Maintained by Aaron Lun. Last updated 5 months ago.

datarepresentation infrastructure software

10 stars 6.89 score 26 scripts 1 dependents

bioc

onlineFDR:Online error rate control

This package allows users to control the false discovery rate (FDR) or familywise error rate (FWER) for online multiple hypothesis testing, where hypotheses arrive in a stream. In this framework, a null hypothesis is rejected based on the evidence against it and on the previous rejection decisions.

Maintained by David S. Robertson. Last updated 5 months ago.

multiplecomparison software statisticalmethod error-rate-control fdr fwer hypothesis-testing cpp

14 stars 6.88 score 26 scripts

bioc

MPRAnalyze:Statistical Analysis of MPRA data

MPRAnalyze provides statistical framework for the analysis of data generated by Massively Parallel Reporter Assays (MPRAs), used to directly measure enhancer activity. MPRAnalyze can be used for quantification of enhancer activity, classification of active enhancers and comparative analyses of enhancer activity between conditions. MPRAnalyze construct a nested pair of generalized linear models (GLMs) to relate the DNA and RNA observations, easily adjustable to various experimental designs and conditions, and provides a set of rigorous statistical testig schemes.

Maintained by Tal Ashuach. Last updated 5 months ago.

immunooncology software statisticalmethod sequencing geneexpression cellbiology cellbasedassays differentialexpression experimentaldesign classification

12 stars 6.86 score 30 scripts

bioc

BioTIP:BioTIP: An R package for characterization of Biological Tipping-Point

Adopting tipping-point theory to transcriptome profiles to unravel disease regulatory trajectory.

Maintained by Yuxi (Jennifer) Sun. Last updated 5 months ago.

sequencing rnaseq geneexpression transcription software

18 stars 6.84 score 37 scripts

bioc

ResidualMatrix:Creating a DelayedMatrix of Regression Residuals

Provides delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. Also supports partial computation of residuals where selected factors are to be preserved in the output matrix. Implements a number of efficient methods for operating on the delayed matrix of residuals, most notably matrix multiplication and calculation of row/column sums or means.

Maintained by Aaron Lun. Last updated 3 months ago.

software datarepresentation regression batcheffect experimentaldesign

1 stars 6.83 score 6 scripts 10 dependents

bioc

MicrobiomeProfiler:An R/shiny package for microbiome functional enrichment analysis

This is an R/shiny package to perform functional enrichment analysis for microbiome data. This package was based on clusterProfiler. Moreover, MicrobiomeProfiler support KEGG enrichment analysis, COG enrichment analysis, Microbe-Disease association enrichment analysis, Metabo-Pathway analysis.

Maintained by Guangchuang Yu. Last updated 5 months ago.

microbiome software visualization kegg

38 stars 6.80 score 22 scripts

bioc

GOexpress:Visualise microarray and RNAseq data using gene ontology annotations

The package contains methods to visualise the expression profile of genes from a microarray or RNA-seq experiment, and offers a supervised clustering approach to identify GO terms containing genes with expression levels that best classify two or more predefined groups of samples. Annotations for the genes present in the expression dataset may be obtained from Ensembl through the biomaRt package, if not provided by the user. The default random forest framework is used to evaluate the capacity of each gene to cluster samples according to the factor of interest. Finally, GO terms are scored by averaging the rank (alternatively, score) of their respective gene sets to cluster the samples. P-values may be computed to assess the significance of GO term ranking. Visualisation function include gene expression profile, gene ontology-based heatmaps, and hierarchical clustering of experimental samples using gene expression data.

Maintained by Kevin Rue-Albrecht. Last updated 5 months ago.

software geneexpression transcription differentialexpression genesetenrichment datarepresentation clustering timecourse microarray sequencing rnaseq annotation multiplecomparison pathways go visualization immunooncology bioconductor bioconductor-package bioconductor-stats geneontology geneset-enrichment

9 stars 6.75 score 31 scripts

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

23 stars 6.74 score 10 scripts

bioc

escheR:Unified multi-dimensional visualizations with Gestalt principles

The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide this open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.

Maintained by Boyi Guo. Last updated 5 months ago.

spatial singlecell transcriptomics visualization software multidimensional single-cell spatial-omics

6 stars 6.74 score 153 scripts 1 dependents

bioc

ROTS:Reproducibility-Optimized Test Statistic

Calculates the Reproducibility-Optimized Test Statistic (ROTS) for differential testing in omics data.

Maintained by Tomi Suomi. Last updated 2 months ago.

software geneexpression differentialexpression microarray rnaseq proteomics immunooncology cpp

6.73 score 86 scripts 3 dependents

bioc

CytoPipeline:Automation and visualization of flow cytometry data analysis pipelines

This package provides support for automation and visualization of flow cytometry data analysis pipelines. In the current state, the package focuses on the preprocessing and quality control part. The framework is based on two main S4 classes, i.e. CytoPipeline and CytoProcessingStep. The pipeline steps are linked to corresponding R functions - that are either provided in the CytoPipeline package itself, or exported from a third party package, or coded by the user her/himself. The processing steps need to be specified centrally and explicitly using either a json input file or through step by step creation of a CytoPipeline object with dedicated methods. After having run the pipeline, obtained results at all steps can be retrieved and visualized thanks to file caching (the running facility uses a BiocFileCache implementation). The package provides also specific visualization tools like pipeline workflow summary display, and 1D/2D comparison plots of obtained flowFrames at various steps of the pipeline.

Maintained by Philippe Hauchamps. Last updated 5 months ago.

flowcytometry preprocessing qualitycontrol workflowstep immunooncology software visualization

4 stars 6.71 score 18 scripts 2 dependents

bioc

rawDiag:Brings Orbitrap Mass Spectrometry Data to Life; Fast and Colorful

Optimizing methods for liquid chromatography coupled to mass spectrometry (LC-MS) poses a nontrivial challenge. The rawDiag package facilitates rational method optimization by generating MS operator-tailored diagnostic plots of scan-level metadata. The package is designed for use on the R shell or as a Shiny application on the Orbitrap instrument PC.

Maintained by Christian Panse. Last updated 5 months ago.

massspectrometry proteomics metabolomics infrastructure software shinyapps fast mass-spectrometry multiplatform orbitrap visualization

36 stars 6.71 score 18 scripts

bioc

syntenet:Inference And Analysis Of Synteny Networks

syntenet can be used to infer synteny networks from whole-genome protein sequences and analyze them. Anchor pairs are detected with the MCScanX algorithm, which was ported to this package with the Rcpp framework for R and C++ integration. Anchor pairs from synteny analyses are treated as an undirected unweighted graph (i.e., a synteny network), and users can perform: i. network clustering; ii. phylogenomic profiling (by identifying which species contain which clusters) and; iii. microsynteny-based phylogeny reconstruction with maximum likelihood.

Maintained by Fabrício Almeida-Silva. Last updated 3 months ago.

software networkinference functionalgenomics comparativegenomics phylogenetics systemsbiology graphandnetwork wholegenome network comparative-genomics evolutionary-genomics network-science phylogenomics synteny synteny-network cpp

28 stars 6.70 score 12 scripts 1 dependents

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

25 stars 6.70 score 6 scripts

bioc

megadepth:megadepth: BigWig and BAM related utilities

This package provides an R interface to Megadepth by Christopher Wilks available at https://github.com/ChristopherWilks/megadepth. It is particularly useful for computing the coverage of a set of genomic regions across bigWig or BAM files. With this package, you can build base-pair coverage matrices for regions or annotations of your choice from BigWig files. Megadepth was used to create the raw files provided by https://bioconductor.org/packages/recount3.

Maintained by David Zhang. Last updated 4 months ago.

software coverage dataimport transcriptomics rnaseq preprocessing bam bigwig daspter megadepth recount2 recount3

12 stars 6.69 score 7 scripts 3 dependents

bioc

tRNA:Analyzing tRNA sequences and structures

The tRNA package allows tRNA sequences and structures to be accessed and used for subsetting. In addition, it provides visualization tools to compare feature parameters of multiple tRNA sets and correlate them to additional data. The tRNA package uses GRanges objects as inputs requiring only few additional column data sets.

Maintained by Felix GM Ernst. Last updated 5 months ago.

software visualization bioconductor sequences structures trna

1 stars 6.69 score 3 scripts 3 dependents

bioc

AnVILBase:Generic functions for interacting with the AnVIL ecosystem

Provides generic functions for interacting with the AnVIL ecosystem. Packages that use either GCP or Azure in AnVIL are built on top of AnVILBase. Extension packages will provide methods for interacting with other cloud providers.

Maintained by Marcel Ramos. Last updated 5 months ago.

software infrastructure

6.68 score 70 scripts 19 dependents

bioc

SpotSweeper:Spatially-aware quality control for spatial transcriptomics

Spatially-aware quality control (QC) software for both spot-level and artifact-level QC in spot-based spatial transcripomics, such as 10x Visium. These methods calculate local (nearest-neighbors) mean and variance of standard QC metrics (library size, unique genes, and mitochondrial percentage) to identify outliers spot and large technical artifacts.

Maintained by Michael Totty. Last updated 3 months ago.

software spatial transcriptomics qualitycontrol geneexpression bioconductor quality-control spatial-transcriptomics

5 stars 6.66 score 77 scripts

bioc

DiffLogo:DiffLogo: A comparative visualisation of biooligomer motifs

DiffLogo is an easy-to-use tool to visualize motif differences.

Maintained by Hendrik Treutler. Last updated 5 months ago.

software sequencematching multiplecomparison motifannotation visualization alignment

8 stars 6.66 score 27 scripts

bioc

RedeR:Interactive visualization and manipulation of nested networks

RedeR is an R-based package combined with a stand-alone Java application for interactive visualization and manipulation of nested networks. Graph, node, and edge attributes can be configured using either graphical or command-line methods, following igraph syntax rules.

Maintained by Mauro Castro. Last updated 5 months ago.

gui graphandnetwork network networkenrichment networkinference software systemsbiology

6.65 score 107 scripts 7 dependents

bioc

ViSEAGO:ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity

The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental design with multiple comparisons of interest. It allows to study large-scale datasets together and visualize GO profiles to capture biological knowledge. The acronym stands for three major concepts of the analysis: Visualization, Semantic similarity and Enrichment Analysis of Gene Ontology. It provides access to the last current GO annotations, which are retrieved from one of NCBI EntrezGene, Ensembl or Uniprot databases for several species. Using available R packages and novel developments, ViSEAGO extends classical functional GO analysis to focus on functional coherence by aggregating closely related biological themes while studying multiple datasets at once. It provides both a synthetic and detailed view using interactive functionalities respecting the GO graph structure and ensuring functional coherence supplied by semantic similarity. ViSEAGO has been successfully applied on several datasets from different species with a variety of biological questions. Results can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility.

Maintained by Aurelien Brionne. Last updated 3 months ago.

software annotation go genesetenrichment multiplecomparison clustering visualization

6.64 score 22 scripts

bioc

miaSim:Microbiome Data Simulation

Microbiome time series simulation with generalized Lotka-Volterra model, Self-Organized Instability (SOI), and other models. Hubbell's Neutral model is used to determine the abundance matrix. The resulting abundance matrix is applied to (Tree)SummarizedExperiment objects.

Maintained by Yagmur Simsek. Last updated 5 months ago.

microbiome software sequencing dnaseq atacseq coverage network

21 stars 6.64 score 23 scripts

bioc

Modstrings:Working with modified nucleotide sequences

Representing nucleotide modifications in a nucleotide sequence is usually done via special characters from a number of sources. This represents a challenge to work with in R and the Biostrings package. The Modstrings package implements this functionallity for RNA and DNA sequences containing modified nucleotides by translating the character internally in order to work with the infrastructure of the Biostrings package. For this the ModRNAString and ModDNAString classes and derivates and functions to construct and modify these objects despite the encoding issues are implemenented. In addition the conversion from sequences to list like location information (and the reverse operation) is implemented as well.

Maintained by Felix G.M. Ernst. Last updated 5 months ago.

dataimport datarepresentation infrastructure sequencing software bioconductor biostrings dna dna-modifications modified-nucleotides nucleotides rna rna-modification-alphabet rna-modifications sequences

1 stars 6.64 score 5 scripts 8 dependents

stefanocoretta

speakr:A Wrapper for the Phonetic Software 'Praat'

It allows running 'Praat' scripts from R and it provides some wrappers for basic plotting. It also adds support for literate markdown tangling. The package is designed to bring reproducible phonetic research into R.

Maintained by Stefano Coretta. Last updated 22 days ago.

praat praatscript software

25 stars 6.63 score 19 scripts

bioc

LEA:LEA: an R package for Landscape and Ecological Association Studies

LEA is an R package dedicated to population genomics, landscape genomics and genotype-environment association tests. LEA can run analyses of population structure and genome-wide tests for local adaptation, and also performs imputation of missing genotypes. The package includes statistical methods for estimating ancestry coefficients from large genotypic matrices and for evaluating the number of ancestral populations (snmf). It performs statistical tests using latent factor mixed models for identifying genetic polymorphisms that exhibit association with environmental gradients or phenotypic traits (lfmm2). In addition, LEA computes values of genetic offset statistics based on new or predicted environments (genetic.gap, genetic.offset). LEA is mainly based on optimized programs that can scale with the dimensions of large data sets.

Maintained by Olivier Francois. Last updated 18 days ago.

software statistical method clustering regression openblas

6.63 score 534 scripts

bioc

BumpyMatrix:Bumpy Matrix of Non-Scalar Objects

Implements the BumpyMatrix class and several subclasses for holding non-scalar objects in each entry of the matrix. This is akin to a ragged array but the raggedness is in the third dimension, much like a bumpy surface - hence the name. Of particular interest is the BumpyDataFrameMatrix, where each entry is a Bioconductor data frame. This allows us to naturally represent multivariate data in a format that is compatible with two-dimensional containers like the SummarizedExperiment and MultiAssayExperiment objects.

Maintained by Aaron Lun. Last updated 3 months ago.

software infrastructure datarepresentation

1 stars 6.62 score 39 scripts 12 dependents

bioc

PepsNMR:Pre-process 1H-NMR FID signals

This package provides R functions for common pre-procssing steps that are applied on 1H-NMR data. It also provides a function to read the FID signals directly in the Bruker format.

Maintained by Manon Martin. Last updated 5 months ago.

software preprocessing visualization metabolomics dataimport

10 stars 6.62 score 23 scripts 1 dependents

bioc

scAnnotatR:Pretrained learning models for cell type prediction on single cell RNA-sequencing data

The package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables all users to quickly get a first annotation of the cell types present in their dataset without requiring prior knowledge. scAnnotatR also allows users to train their own models to predict new cell types based on specific research needs.

Maintained by Johannes Griss. Last updated 5 months ago.

singlecell transcriptomics geneexpression supportvectormachine classification software

15 stars 6.61 score 20 scripts

bioc

MSstatsTMT:Protein Significance Analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling

The package provides statistical tools for detecting differentially abundant proteins in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling. It provides multiple functionalities, including aata visualization, protein quantification and normalization, and statistical modeling and inference. Furthermore, it is inter-operable with other data processing tools, such as Proteome Discoverer, MaxQuant, OpenMS and SpectroMine.

Maintained by Devon Kohler. Last updated 24 days ago.

immunooncology massspectrometry proteomics software

6.60 score 35 scripts 3 dependents

bioc

simona:Semantic Similarity on Bio-Ontologies

This package implements infrastructures for ontology analysis by offering efficient data structures, fast ontology traversal methods, and elegant visualizations. It provides a robust toolbox supporting over 70 methods for semantic similarity analysis.

Maintained by Zuguang Gu. Last updated 5 months ago.

software annotation go biomedicalinformatics cpp

16 stars 6.59 score 27 scripts 1 dependents

bioc

scds:In-Silico Annotation of Doublets for Single Cell RNA Sequencing Data

In single cell RNA sequencing (scRNA-seq) data combinations of cells are sometimes considered a single cell (doublets). The scds package provides methods to annotate doublets in scRNA-seq data computationally.

Maintained by Dennis Kostka. Last updated 5 months ago.

singlecell rnaseq qualitycontrol preprocessing transcriptomics geneexpression sequencing software classification

6.57 score 176 scripts 1 dependents

bioc

SpaceMarkers:Spatial Interaction Markers

Spatial transcriptomic technologies have helped to resolve the connection between gene expression and the 2D orientation of tissues relative to each other. However, the limited single-cell resolution makes it difficult to highlight the most important molecular interactions in these tissues. SpaceMarkers, R/Bioconductor software, can help to find molecular interactions, by identifying genes associated with latent space interactions in spatial transcriptomics.

Maintained by Atul Deshpande. Last updated 12 days ago.

singlecell geneexpression software spatial transcriptomics

5 stars 6.55 score 21 scripts

bioc

tricycle:tricycle: Transferable Representation and Inference of cell cycle

The package contains functions to infer and visualize cell cycle process using Single Cell RNASeq data. It exploits the idea of transfer learning, projecting new data to the previous learned biologically interpretable space. We provide a pre-learned cell cycle space, which could be used to infer cell cycle time of human and mouse single cell samples. In addition, we also offer functions to visualize cell cycle time on different embeddings and functions to build new reference.

Maintained by Shijie Zheng. Last updated 5 months ago.

singlecell software transcriptomics rnaseq transcription biologicalquestion dimensionreduction immunooncology

25 stars 6.54 score 46 scripts

bioc

SpectralTAD:SpectralTAD: Hierarchical TAD detection using spectral clustering

SpectralTAD is an R package designed to identify Topologically Associated Domains (TADs) from Hi-C contact matrices. It uses a modified version of spectral clustering that uses a sliding window to quickly detect TADs. The function works on a range of different formats of contact matrices and returns a bed file of TAD coordinates. The method does not require users to adjust any parameters to work and gives them control over the number of hierarchical levels to be returned.

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing featureextraction clustering

8 stars 6.53 score 17 scripts

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 4 months ago.

rnaseq sequencing software singlecell transcriptomics multiplecomparison visualization

26 stars 6.52 score 17 scripts

bioc

nipalsMCIA:Multiple Co-Inertia Analysis via the NIPALS Method

Computes Multiple Co-Inertia Analysis (MCIA), a dimensionality reduction (jDR) algorithm, for a multi-block dataset using a modification to the Nonlinear Iterative Partial Least Squares method (NIPALS) proposed in (Hanafi et. al, 2010). Allows multiple options for row- and table-level preprocessing, and speeds up computation of variance explained. Vignettes detail application to bulk- and single cell- multi-omics studies.

Maintained by Maximilian Mattessich. Last updated 1 months ago.

software clustering classification multiplecomparison normalization preprocessing singlecell

6 stars 6.51 score 10 scripts

bioc

miRBaseConverter:A comprehensive and high-efficiency tool for converting and retrieving the information of miRNAs in different miRBase versions

A comprehensive tool for converting and retrieving the miRNA Name, Accession, Sequence, Version, History and Family information in different miRBase versions. It can process a huge number of miRNAs in a short time without other depends.

Maintained by Taosheng Xu Taosheng Xu. Last updated 5 months ago.

software mirna

1 stars 6.50 score 70 scripts

bioc

Prostar:Provides a GUI for DAPAR

This package provides a GUI interface for the DAPAR package. The package Prostar (Proteomics statistical analysis with R) 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.

Maintained by Samuel Wieczorek. Last updated 5 months ago.

proteomics massspectrometry normalization preprocessing software gui prostar1

1 stars 6.48 score 15 scripts