R-universe search: needs:S4Vectors

bioc

Biostrings:Efficient manipulation of biological strings

Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences.

Maintained by Hervé Pagès. Last updated 1 months ago.

sequencematching alignment sequencing genetics dataimport datarepresentation infrastructure bioconductor-package core-package

62 stars 17.77 score 8.6k scripts 1.2k dependents

bioc

GenomicRanges:Representation and manipulation of genomic intervals

The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome. More specialized containers for representing and manipulating short alignments against a reference genome, or a matrix-like summarization of an experiment, are defined in the GenomicAlignments and SummarizedExperiment packages, respectively. Both packages build on top of the GenomicRanges infrastructure.

Maintained by Hervé Pagès. Last updated 5 months ago.

genetics infrastructure datarepresentation sequencing annotation genomeannotation coverage bioconductor-package core-package

44 stars 17.68 score 13k scripts 1.3k dependents

bioc

clusterProfiler:A universal enrichment tool for interpreting omics data

This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios. It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation. Datasets obtained from multiple treatments and time points can be analyzed and compared in a single run, easily revealing functional consensus and differences among distinct conditions.

Maintained by Guangchuang Yu. Last updated 4 months ago.

annotation clustering genesetenrichment go kegg multiplecomparison pathways reactome visualization enrichment-analysis gsea

1.1k stars 17.03 score 11k scripts 48 dependents

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

SummarizedExperiment:A container (S4 class) for matrix-like assays

The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.

Maintained by Hervé Pagès. Last updated 5 months ago.

genetics infrastructure sequencing annotation coverage genomeannotation bioconductor-package core-package

34 stars 16.84 score 8.6k scripts 1.2k dependents

bioc

GenomeInfoDb:Utilities for manipulating chromosome names, including modifying them to follow a particular naming style

Contains data and functions that define and allow translation between different chromosome sequence naming conventions (e.g., "chr1" versus "1"), including a function that attempts to place sequence names in their natural, rather than lexicographic, order.

Maintained by Hervé Pagès. Last updated 2 months ago.

genetics datarepresentation annotation genomeannotation bioconductor-package core-package

32 stars 16.32 score 1.3k scripts 1.7k dependents

bioc

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

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

Maintained by Michael Love. Last updated 27 days ago.

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

375 stars 16.11 score 17k scripts 115 dependents

bioc

IRanges:Foundation of integer range manipulation in Bioconductor

Provides efficient low-level and highly reusable S4 classes for storing, manipulating and aggregating over annotated ranges of integers. Implements an algebra of range operations, including efficient algorithms for finding overlaps and nearest neighbors. Defines efficient list-like classes for storing, transforming and aggregating large grouped data, i.e., collections of atomic vectors and DataFrames.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure datarepresentation bioconductor-package core-package

22 stars 16.09 score 2.1k scripts 1.8k dependents

bioc

biomaRt:Interface to BioMart databases (i.e. Ensembl)

In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (<http://www.biomart.org>). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. The most prominent examples of BioMart databases are maintain by Ensembl, which provides biomaRt users direct access to a diverse set of data and enables a wide range of powerful online queries from gene annotation to database mining.

Maintained by Mike Smith. Last updated 18 days ago.

annotation bioconductor biomart ensembl

38 stars 15.99 score 13k scripts 230 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

DelayedArray:A unified framework for working transparently with on-disk and in-memory array-like datasets

Wrapping an array-like object (typically an on-disk object) in a DelayedArray object allows one to perform common array operations on it without loading the object in memory. In order to reduce memory usage and optimize performance, operations on the object are either delayed or executed using a block processing mechanism. Note that this also works on in-memory array-like objects like DataFrame objects (typically with Rle columns), Matrix objects, ordinary arrays and, data frames.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure datarepresentation annotation genomeannotation bioconductor-package core-package u24ca289073

27 stars 15.59 score 538 scripts 1.2k dependents

bioc

Rsamtools:Binary alignment (BAM), FASTA, variant call (BCF), and tabix file import

This package provides an interface to the 'samtools', 'bcftools', and 'tabix' utilities for manipulating SAM (Sequence Alignment / Map), FASTA, binary variant call (BCF) and compressed indexed tab-delimited (tabix) files.

Maintained by Bioconductor Package Maintainer. Last updated 4 months ago.

dataimport sequencing coverage alignment qualitycontrol bioconductor-package core-package curl bzip2 xz-utils zlib cpp

28 stars 15.34 score 3.2k scripts 569 dependents

bioc

GenomicFeatures:Query the gene models of a given organism/assembly

Extract the genomic locations of genes, transcripts, exons, introns, and CDS, for the gene models stored in a TxDb object. A TxDb object is a small database that contains the gene models of a given organism/assembly. Bioconductor provides a small collection of TxDb objects in the form of ready-to-install TxDb packages for the most commonly studied organisms. Additionally, the user can easily make a TxDb object (or package) for the organism/assembly of their choice by using the tools from the txdbmaker package.

Maintained by H. Pagès. Last updated 5 months ago.

genetics infrastructure annotation sequencing genomeannotation bioconductor-package core-package

26 stars 15.34 score 5.3k scripts 339 dependents

bioc

GenomicAlignments:Representation and manipulation of short genomic alignments

Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working with the nucleotide content of the alignments.

Maintained by Hervé Pagès. Last updated 5 months ago.

infrastructure dataimport genetics sequencing rnaseq snp coverage alignment immunooncology bioconductor-package core-package

10 stars 15.21 score 3.1k scripts 528 dependents

bioc

AnnotationDbi:Manipulation of SQLite-based annotations in Bioconductor

Implements a user-friendly interface for querying SQLite-based annotation data packages.

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

annotation microarray sequencing genomeannotation bioconductor-package core-package

9 stars 15.05 score 3.6k scripts 769 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

MultiAssayExperiment:Software for the integration of multi-omics experiments in Bioconductor

Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.

Maintained by Marcel Ramos. Last updated 2 months ago.

infrastructure datarepresentation bioconductor bioconductor-package genomics nci-itcr tcga u24ca289073

71 stars 14.94 score 670 scripts 126 dependents

bioc

GSVA:Gene Set Variation Analysis for Microarray and RNA-Seq Data

Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner.

Maintained by Robert Castelo. Last updated 11 days ago.

functionalgenomics microarray rnaseq pathways genesetenrichment gene-set-enrichment genomics pathway-enrichment-analysis

212 stars 14.74 score 1.6k scripts 19 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

xcms:LC-MS and GC-MS Data Analysis

Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.

Maintained by Steffen Neumann. Last updated 18 days ago.

immunooncology massspectrometry metabolomics bioconductor feature-detection mass-spectrometry peak-detection cpp

196 stars 14.31 score 984 scripts 11 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

BSgenome:Software infrastructure for efficient representation of full genomes and their SNPs

Infrastructure shared by all the Biostrings-based genome data packages.

Maintained by Hervé Pagès. Last updated 2 months ago.

genetics infrastructure datarepresentation sequencematching annotation snp bioconductor-package core-package

9 stars 14.12 score 1.2k scripts 267 dependents

bioc

ensembldb:Utilities to create and use Ensembl-based annotation databases

The package provides functions to create and use transcript centric annotation databases/packages. The annotation for the databases are directly fetched from Ensembl using their Perl API. The functionality and data is similar to that of the TxDb packages from the GenomicFeatures package, but, in addition to retrieve all gene/transcript models and annotations from the database, ensembldb provides a filter framework allowing to retrieve annotations for specific entries like genes encoded on a chromosome region or transcript models of lincRNA genes. EnsDb databases built with ensembldb contain also protein annotations and mappings between proteins and their encoding transcripts. Finally, ensembldb provides functions to map between genomic, transcript and protein coordinates.

Maintained by Johannes Rainer. Last updated 5 months ago.

genetics annotationdata sequencing coverage annotation bioconductor bioconductor-packages ensembl

35 stars 14.08 score 892 scripts 108 dependents

bioc

phyloseq:Handling and analysis of high-throughput microbiome census data

phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.

Maintained by Paul J. McMurdie. Last updated 5 months ago.

immunooncology sequencing microbiome metagenomics clustering classification multiplecomparison geneticvariability

600 stars 13.91 score 8.4k scripts 38 dependents

bioc

AnnotationHub:Client to access AnnotationHub resources

This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, Ensembl) can be discovered. The resource includes metadata about each resource, e.g., a textual description, tags, and date of modification. The client creates and manages a local cache of files retrieved by the user, helping with quick and reproducible access.

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

infrastructure dataimport gui thirdpartyclient core-package u24ca289073

17 stars 13.88 score 2.7k scripts 104 dependents

bioc

SingleCellExperiment:S4 Classes for Single Cell Data

Defines a S4 class for storing data from single-cell experiments. This includes specialized methods to store and retrieve spike-in information, dimensionality reduction coordinates and size factors for each cell, along with the usual metadata for genes and libraries.

Maintained by Davide Risso. Last updated 25 days ago.

immunooncology datarepresentation dataimport infrastructure singlecell

13.53 score 15k scripts 285 dependents

bioc

KEGGREST:Client-side REST access to the Kyoto Encyclopedia of Genes and Genomes (KEGG)

A package that provides a client interface to the Kyoto Encyclopedia of Genes and Genomes (KEGG) REST API. Only for academic use by academic users belonging to academic institutions (see <https://www.kegg.jp/kegg/rest/>). Note that KEGGREST is based on KEGGSOAP by J. Zhang, R. Gentleman, and Marc Carlson, and KEGG (python package) by Aurelien Mazurie.

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

annotation pathways thirdpartyclient kegg bioconductor-package core-package

10 stars 13.50 score 688 scripts 771 dependents

bioc

GEOquery:Get data from NCBI Gene Expression Omnibus (GEO)

The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor.

Maintained by Sean Davis. Last updated 5 months ago.

microarray dataimport onechannel twochannel sage bioconductor bioinformatics data-science genomics ncbi-geo

93 stars 13.48 score 4.1k scripts 45 dependents

bioc

HDF5Array:HDF5 datasets as array-like objects in R

The HDF5Array package is an HDF5 backend for DelayedArray objects. It implements the HDF5Array, H5SparseMatrix, H5ADMatrix, and TENxMatrix classes, 4 convenient and memory-efficient array-like containers for representing and manipulating either: (1) a conventional (a.k.a. dense) HDF5 dataset, (2) an HDF5 sparse matrix (stored in CSR/CSC/Yale format), (3) the central matrix of an h5ad file (or any matrix in the /layers group), or (4) a 10x Genomics sparse matrix. All these containers are DelayedArray extensions and thus support all operations (delayed or block-processed) supported by DelayedArray objects.

Maintained by Hervé Pagès. Last updated 13 days ago.

infrastructure datarepresentation dataimport sequencing rnaseq coverage annotation genomeannotation singlecell immunooncology bioconductor-package core-package u24ca289073

12 stars 13.20 score 844 scripts 126 dependents

bioc

dada2:Accurate, high-resolution sample inference from amplicon sequencing data

The dada2 package infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.

Maintained by Benjamin Callahan. Last updated 5 months ago.

immunooncology microbiome sequencing classification metagenomics amplicon bioconductor bioinformatics metabarcoding taxonomy cpp

487 stars 13.17 score 3.0k scripts 4 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

Gviz:Plotting data and annotation information along genomic coordinates

Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data.

Maintained by Robert Ivanek. Last updated 5 months ago.

visualization microarray sequencing

79 stars 13.05 score 1.4k scripts 46 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

Spectra:Spectra Infrastructure for Mass Spectrometry Data

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

Maintained by RforMassSpectrometry Package Maintainer. Last updated 25 days ago.

infrastructure proteomics massspectrometry metabolomics bioconductor hacktoberfest mass-spectrometry

41 stars 13.01 score 254 scripts 35 dependents

bioc

iSEE:Interactive SummarizedExperiment Explorer

Create an interactive Shiny-based graphical user interface for exploring data stored in SummarizedExperiment objects, including row- and column-level metadata. The interface supports transmission of selections between plots and tables, code tracking, interactive tours, interactive or programmatic initialization, preservation of app state, and extensibility to new panel types via S4 classes. Special attention is given to single-cell data in a SingleCellExperiment object with visualization of dimensionality reduction results.

Maintained by Kevin Rue-Albrecht. Last updated 26 days ago.

cellbasedassays clustering dimensionreduction featureextraction geneexpression gui immunooncology shinyapps singlecell transcription transcriptomics visualization dimension-reduction feature-extraction gene-expression hacktoberfest human-cell-atlas shiny single-cell

225 stars 12.86 score 380 scripts 9 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 2 months ago.

software singlecell geneexpression transcriptomics classification clustering annotation bioconductor singler cpp

184 stars 12.83 score 2.1k scripts 2 dependents

bioc

minfi:Analyze Illumina Infinium DNA methylation arrays

Tools to analyze & visualize Illumina Infinium methylation arrays.

Maintained by Kasper Daniel Hansen. Last updated 4 months ago.

immunooncology dnamethylation differentialmethylation epigenetics microarray methylationarray multichannel twochannel dataimport normalization preprocessing qualitycontrol

60 stars 12.82 score 996 scripts 27 dependents

bioc

MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics

MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.

Maintained by Laurent Gatto. Last updated 18 days ago.

immunooncology infrastructure proteomics massspectrometry qualitycontrol dataimport bioconductor bioinformatics mass-spectrometry proteomics-data visualisation cpp

131 stars 12.76 score 772 scripts 36 dependents

bioc

plyranges:A fluent interface for manipulating GenomicRanges

A dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessiblity for new Bioconductor users is hopefully increased.

Maintained by Michael Love. Last updated 13 days ago.

infrastructure datarepresentation workflowstep coverage bioconductor data-analysis dplyr genomic-ranges genomics tidy-data

144 stars 12.66 score 1.9k scripts 20 dependents

bioc

rtracklayer:R interface to genome annotation files and the UCSC genome browser

Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/import tracks to/from the supported browsers, as well as query and modify the browser state, such as the current viewport.

Maintained by Michael Lawrence. Last updated 7 days ago.

annotation visualization dataimport zlib openssl curl

12.66 score 6.7k scripts 480 dependents

bioc

SpatialExperiment:S4 Class for Spatially Resolved -omics Data

Defines an S4 class for storing data from spatial -omics experiments. The class extends SingleCellExperiment to support storage and retrieval of additional information from spot-based and molecule-based platforms, including spatial coordinates, images, and image metadata. A specialized constructor function is included for data from the 10x Genomics Visium platform.

Maintained by Dario Righelli. Last updated 5 months ago.

datarepresentation dataimport infrastructure immunooncology geneexpression transcriptomics singlecell spatial

59 stars 12.63 score 1.8k scripts 71 dependents

bioc

microbiome:Microbiome Analytics

Utilities for microbiome analysis.

Maintained by Leo Lahti. Last updated 5 months ago.

metagenomics microbiome sequencing systemsbiology hitchip hitchip-atlas human-microbiome microbiology microbiome-analysis phyloseq population-study

293 stars 12.51 score 2.0k scripts 5 dependents

bioc

SparseArray:High-performance sparse data representation and manipulation in R

The SparseArray package provides array-like containers for efficient in-memory representation of multidimensional sparse data in R (arrays and matrices). The package defines the SparseArray virtual class and two concrete subclasses: COO_SparseArray and SVT_SparseArray. Each subclass uses its own internal representation of the nonzero multidimensional data: the "COO layout" and the "SVT layout", respectively. SVT_SparseArray objects mimic as much as possible the behavior of ordinary matrix and array objects in base R. In particular, they suppport most of the "standard matrix and array API" defined in base R and in the matrixStats package from CRAN.

Maintained by Hervé Pagès. Last updated 14 days ago.

infrastructure datarepresentation bioconductor-package core-package openmp

9 stars 12.47 score 79 scripts 1.2k dependents

bioc

scDblFinder:scDblFinder

The scDblFinder package gathers various methods for the detection and handling of doublets/multiplets in single-cell sequencing data (i.e. multiple cells captured within the same droplet or reaction volume). It includes methods formerly found in the scran package, the new fast and comprehensive scDblFinder method, and a reimplementation of the Amulet detection method for single-cell ATAC-seq.

Maintained by Pierre-Luc Germain. Last updated 13 days ago.

preprocessing singlecell rnaseq atacseq doublets single-cell

184 stars 12.38 score 888 scripts 1 dependents

bioc

TFBSTools:Software Package for Transcription Factor Binding Site (TFBS) Analysis

TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matirx (PFM), Position Weight Matirx (PWM) and Information Content Matrix (ICM). It can also scan putative TFBS from sequence/alignment, query JASPAR database and provides a wrapper of de novo motif discovery software.

Maintained by Ge Tan. Last updated 20 days ago.

motifannotation generegulation motifdiscovery transcription alignment

28 stars 12.36 score 1.1k scripts 18 dependents

bioc

bsseq:Analyze, manage and store whole-genome methylation data

A collection of tools for analyzing and visualizing whole-genome methylation data from sequencing. This includes whole-genome bisulfite sequencing and Oxford nanopore data.

Maintained by Kasper Daniel Hansen. Last updated 4 months ago.

dnamethylation cpp

37 stars 12.26 score 676 scripts 15 dependents

bioc

ReactomePA:Reactome Pathway Analysis

This package provides functions for pathway analysis based on REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization. This package is not affiliated with the Reactome team.

Maintained by Guangchuang Yu. Last updated 5 months ago.

pathways visualization annotation multiplecomparison genesetenrichment reactome enrichment-analysis reactome-pathway-analysis reactomepa

40 stars 12.25 score 1.5k scripts 7 dependents

bioc

ggbio:Visualization tools for genomic data

The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.

Maintained by Michael Lawrence. Last updated 5 months ago.

infrastructure visualization

111 stars 12.23 score 734 scripts 16 dependents

stuart-lab

Signac:Analysis of Single-Cell Chromatin Data

A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2021) <doi:10.1038/s41592-021-01282-5>.

Maintained by Tim Stuart. Last updated 7 months ago.

atac bioinformatics single-cell zlib cpp

355 stars 12.18 score 3.7k scripts 1 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 15 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

SeqArray:Data management of large-scale whole-genome sequence variant calls using GDS files

Data management of large-scale whole-genome sequencing variant calls with thousands of individuals: genotypic data (e.g., SNVs, indels and structural variation calls) and annotations in SeqArray GDS files are stored in an array-oriented and compressed manner, with efficient data access using the R programming language.

Maintained by Xiuwen Zheng. Last updated 9 days ago.

infrastructure datarepresentation sequencing genetics bioinformatics gds-format snp snv wes wgs cpp

45 stars 12.11 score 1.1k scripts 9 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

ShortRead:FASTQ input and manipulation

This package implements sampling, iteration, and input of FASTQ files. The package includes functions for filtering and trimming reads, and for generating a quality assessment report. Data are represented as DNAStringSet-derived objects, and easily manipulated for a diversity of purposes. The package also contains legacy support for early single-end, ungapped alignment formats.

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

dataimport sequencing qualitycontrol bioconductor-package core-package zlib cpp

8 stars 12.08 score 1.8k scripts 49 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

286 stars 12.01 score 1.0k scripts 4 dependents

bioc

ExperimentHub:Client to access ExperimentHub resources

This package provides a client for the Bioconductor ExperimentHub web resource. ExperimentHub provides a central location where curated data from experiments, publications or training courses can be accessed. Each resource has associated metadata, tags and date of modification. The client creates and manages a local cache of files retrieved enabling quick and reproducible access.

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

infrastructure dataimport gui thirdpartyclient core-package u24ca289073

10 stars 11.94 score 764 scripts 57 dependents

bioc

GenomicDataCommons:NIH / NCI Genomic Data Commons Access

Programmatically access the NIH / NCI Genomic Data Commons RESTful service.

Maintained by Sean Davis. Last updated 2 months ago.

dataimport sequencing api-client bioconductor bioinformatics cancer core-services data-science genomics nci tcga vignette

87 stars 11.94 score 238 scripts 12 dependents

bioc

QFeatures:Quantitative features for mass spectrometry data

The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assay levels (such as peptide spectrum matches, peptides and proteins) in a coherent and tractable format.

Maintained by Laurent Gatto. Last updated 29 days ago.

infrastructure massspectrometry proteomics metabolomics bioconductor mass-spectrometry

27 stars 11.87 score 278 scripts 49 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

bioc

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

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

Maintained by Altuna Akalin. Last updated 1 months ago.

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

224 stars 11.78 score 578 scripts 3 dependents

bioc

bumphunter:Bump Hunter

Tools for finding bumps in genomic data

Maintained by Tamilselvi Guharaj. Last updated 5 months ago.

dnamethylation epigenetics infrastructure multiplecomparison immunooncology

16 stars 11.61 score 210 scripts 43 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 2 days ago.

microbiome software dataimport analysis bioconductor cpp

51 stars 11.52 score 316 scripts 5 dependents

bioc

systemPipeR:systemPipeR: Workflow Environment for Data Analysis and Report Generation

systemPipeR is a multipurpose data analysis workflow environment that unifies R with command-line tools. It enables scientists to analyze many types of large- or small-scale data on local or distributed computer systems with a high level of reproducibility, scalability and portability. At its core is a command-line interface (CLI) that adopts the Common Workflow Language (CWL). This design allows users to choose for each analysis step the optimal R or command-line software. It supports both end-to-end and partial execution of workflows with built-in restart functionalities. Efficient management of complex analysis tasks is accomplished by a flexible workflow control container class. Handling of large numbers of input samples and experimental designs is facilitated by consistent sample annotation mechanisms. As a multi-purpose workflow toolkit, systemPipeR enables users to run existing workflows, customize them or design entirely new ones while taking advantage of widely adopted data structures within the Bioconductor ecosystem. Another important core functionality is the generation of reproducible scientific analysis and technical reports. For result interpretation, systemPipeR offers a wide range of plotting functionality, while an associated Shiny App offers many useful functionalities for interactive result exploration. The vignettes linked from this page include (1) a general introduction, (2) a description of technical details, and (3) a collection of workflow templates.

Maintained by Thomas Girke. Last updated 5 months ago.

genetics infrastructure dataimport sequencing rnaseq riboseq chipseq methylseq snp geneexpression coverage genesetenrichment alignment qualitycontrol immunooncology reportwriting workflowstep workflowmanagement

53 stars 11.52 score 344 scripts 3 dependents

bioc

msa:Multiple Sequence Alignment

The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.

Maintained by Ulrich Bodenhofer. Last updated 2 months ago.

multiplesequencealignment alignment multiplecomparison sequencing cpp

17 stars 11.46 score 744 scripts 6 dependents

bioc

destiny:Creates diffusion maps

Create and plot diffusion maps.

Maintained by Philipp Angerer. Last updated 5 months ago.

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

82 stars 11.44 score 792 scripts 1 dependents

bioc

annotate:Annotation for microarrays

Using R enviroments for annotation.

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

annotation pathways go

11.41 score 812 scripts 239 dependents

bioc

VariantAnnotation:Annotation of Genetic Variants

Annotate variants, compute amino acid coding changes, predict coding outcomes.

Maintained by Bioconductor Package Maintainer. Last updated 3 months ago.

dataimport sequencing snp annotation genetics variantannotation curl bzip2 xz-utils zlib

11.39 score 1.9k scripts 152 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

pathview:a tool set for pathway based data integration and visualization

Pathview is a tool set for pathway based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.

Maintained by Weijun Luo. Last updated 4 days ago.

pathways graphandnetwork visualization genesetenrichment differentialexpression geneexpression microarray rnaseq genetics metabolomics proteomics systemsbiology sequencing

40 stars 11.37 score 1.6k scripts 10 dependents

bioc

XVector:Foundation of external vector representation and manipulation in Bioconductor

Provides memory efficient S4 classes for storing sequences "externally" (e.g. behind an R external pointer, or on disk).

Maintained by Hervé Pagès. Last updated 3 months ago.

infrastructure datarepresentation bioconductor-package core-package zlib

2 stars 11.36 score 67 scripts 1.7k dependents

ropensci

biomartr:Genomic Data Retrieval

Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized way to automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and metagenome retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL', and 'UniProt' databases. Furthermore, an interface to the 'BioMart' database (Smedley et al. (2009) <doi:10.1186/1471-2164-10-22>) allows users to retrieve functional annotation for genomic loci. In addition, users can download entire databases such as 'NCBI RefSeq' (Pruitt et al. (2007) <doi:10.1093/nar/gkl842>), 'NCBI nr', 'NCBI nt', 'NCBI Genbank' (Benson et al. (2013) <doi:10.1093/nar/gks1195>), etc. with only one command.

Maintained by Hajk-Georg Drost. Last updated 2 months ago.

biomart genomic-data-retrieval annotation-retrieval database-retrieval ncbi ensembl biological-data-retrieval ensembl-servers genome genome-annotation genome-retrieval genomics meta-analysis metagenomics ncbi-genbank peer-reviewed proteome sequenced-genomes

218 stars 11.35 score 129 scripts 3 dependents

bioc

MAST:Model-based Analysis of Single Cell Transcriptomics

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

Maintained by Andrew McDavid. Last updated 5 months ago.

geneexpression differentialexpression genesetenrichment rnaseq transcriptomics singlecell

232 stars 11.28 score 1.8k scripts 5 dependents

bioc

ggcyto:Visualize Cytometry data with ggplot

With the dedicated fortify method implemented for flowSet, ncdfFlowSet and GatingSet classes, both raw and gated flow cytometry data can be plotted directly with ggplot. ggcyto wrapper and some customed layers also make it easy to add gates and population statistics to the plot.

Maintained by Mike Jiang. Last updated 5 months ago.

immunooncology flowcytometry cellbasedassays infrastructure visualization

58 stars 11.25 score 362 scripts 5 dependents

bioc

zellkonverter:Conversion Between scRNA-seq Objects

Provides methods to convert between Python AnnData objects and SingleCellExperiment objects. These are primarily intended for use by downstream Bioconductor packages that wrap Python methods for single-cell data analysis. It also includes functions to read and write H5AD files used for saving AnnData objects to disk.

Maintained by Luke Zappia. Last updated 24 days ago.

singlecell dataimport datarepresentation bioconductor conversion scrna-seq

159 stars 11.25 score 660 scripts 4 dependents

bioc

karyoploteR:Plot customizable linear genomes displaying arbitrary data

karyoploteR creates karyotype plots of arbitrary genomes and offers a complete set of functions to plot arbitrary data on them. It mimicks many R base graphics functions coupling them with a coordinate change function automatically mapping the chromosome and data coordinates into the plot coordinates. In addition to the provided data plotting functions, it is easy to add new ones.

Maintained by Bernat Gel. Last updated 5 months ago.

visualization copynumbervariation sequencing coverage dnaseq chipseq methylseq dataimport onechannel bioconductor bioinformatics data-visualization genome genomics-visualization plotting-in-r

307 stars 11.25 score 656 scripts 4 dependents

bioc

genomation:Summary, annotation and visualization of genomic data

A package for summary and annotation of genomic intervals. Users can visualize and quantify genomic intervals over pre-defined functional regions, such as promoters, exons, introns, etc. The genomic intervals represent regions with a defined chromosome position, which may be associated with a score, such as aligned reads from HT-seq experiments, TF binding sites, methylation scores, etc. The package can use any tabular genomic feature data as long as it has minimal information on the locations of genomic intervals. In addition, It can use BAM or BigWig files as input.

Maintained by Altuna Akalin. Last updated 5 months ago.

annotation sequencing visualization cpgisland cpp

76 stars 11.13 score 738 scripts 5 dependents

bioc

PCAtools:PCAtools: Everything Principal Components Analysis

Principal Component Analysis (PCA) is a very powerful technique that has wide applicability in data science, bioinformatics, and further afield. It was initially developed to analyse large volumes of data in order to tease out the differences/relationships between the logical entities being analysed. It extracts the fundamental structure of the data without the need to build any model to represent it. This 'summary' of the data is arrived at through a process of reduction that can transform the large number of variables into a lesser number that are uncorrelated (i.e. the 'principal components'), while at the same time being capable of easy interpretation on the original data. PCAtools provides functions for data exploration via PCA, and allows the user to generate publication-ready figures. PCA is performed via BiocSingular - users can also identify optimal number of principal components via different metrics, such as elbow method and Horn's parallel analysis, which has relevance for data reduction in single-cell RNA-seq (scRNA-seq) and high dimensional mass cytometry data.

Maintained by Kevin Blighe. Last updated 5 months ago.

rnaseq atacseq geneexpression transcription singlecell principalcomponent cpp

348 stars 11.12 score 832 scripts 2 dependents

bioc

genefilter:genefilter: methods for filtering genes from high-throughput experiments

Some basic functions for filtering genes.

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

microarray fortran cpp

11.11 score 2.4k scripts 143 dependents

bioc

beachmat:Compiling Bioconductor to Handle Each Matrix Type

Provides a consistent C++ class interface for reading from a variety of commonly used matrix types. Ordinary matrices and several sparse/dense Matrix classes are directly supported, along with a subset of the delayed operations implemented in the DelayedArray package. All other matrix-like objects are supported by calling back into R.

Maintained by Aaron Lun. Last updated 19 days ago.

datarepresentation dataimport infrastructure bioconductor-package human-cell-atlas matrix-library cpp

4 stars 11.09 score 21 scripts 142 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 25 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

universalmotif:Import, Modify, and Export Motifs with R

Allows for importing most common motif types into R for use by functions provided by other Bioconductor motif-related packages. Motifs can be exported into most major motif formats from various classes as defined by other Bioconductor packages. A suite of motif and sequence manipulation and analysis functions are included, including enrichment, comparison, P-value calculation, shuffling, trimming, higher-order motifs, and others.

Maintained by Benjamin Jean-Marie Tremblay. Last updated 5 months ago.

motifannotation motifdiscovery dataimport generegulation motif-analysis motif-enrichment-analysis sequence-logo cpp

28 stars 11.04 score 342 scripts 12 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

S4Arrays:Foundation of array-like containers in Bioconductor

The S4Arrays package defines the Array virtual class to be extended by other S4 classes that wish to implement a container with an array-like semantic. It also provides: (1) low-level functionality meant to help the developer of such container to implement basic operations like display, subsetting, or coercion of their array-like objects to an ordinary matrix or array, and (2) a framework that facilitates block processing of array-like objects (typically on-disk objects).

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure datarepresentation bioconductor-package core-package

5 stars 10.99 score 8 scripts 1.2k 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

DirichletMultinomial:Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.

Maintained by Martin Morgan. Last updated 5 months ago.

immunooncology microbiome sequencing clustering classification metagenomics gsl

10 stars 10.91 score 125 scripts 26 dependents

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

welch-lab

rliger:Linked Inference of Genomic Experimental Relationships

Uses an extension of nonnegative matrix factorization to identify shared and dataset-specific factors. See Welch J, Kozareva V, et al (2019) <doi:10.1016/j.cell.2019.05.006>, and Liu J, Gao C, Sodicoff J, et al (2020) <doi:10.1038/s41596-020-0391-8> for more details.

Maintained by Yichen Wang. Last updated 3 months ago.

nonnegative-matrix-factorization single-cell openblas cpp

408 stars 10.77 score 334 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

Glimma:Interactive visualizations for gene expression analysis

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

Maintained by Shian Su. Last updated 2 months ago.

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

32 stars 10.58 score 600 scripts 1 dependents

bioc

MsCoreUtils:Core Utils for Mass Spectrometry Data

MsCoreUtils defines low-level functions for mass spectrometry data and is independent of any high-level data structures. These functions include mass spectra processing functions (noise estimation, smoothing, binning, baseline estimation), quantitative aggregation functions (median polish, robust summarisation, ...), missing data imputation, data normalisation (quantiles, vsn, ...), misc helper functions, that are used across high-level data structure within the R for Mass Spectrometry packages.

Maintained by RforMassSpectrometry Package Maintainer. Last updated 11 days ago.

infrastructure proteomics massspectrometry metabolomics bioconductor mass-spectrometry utils

16 stars 10.57 score 41 scripts 71 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

DECIPHER:Tools for curating, analyzing, and manipulating biological sequences

A toolset for deciphering and managing biological sequences.

Maintained by Erik Wright. Last updated 21 days ago.

clustering genetics sequencing dataimport visualization microarray qualitycontrol qpcr alignment wholegenome microbiome immunooncology geneprediction openmp

10.55 score 1.1k scripts 14 dependents

bioc

tximeta:Transcript Quantification Import with Automatic Metadata

Transcript quantification import from Salmon and other quantifiers with automatic attachment of transcript ranges and release information, and other associated metadata. De novo transcriptomes can be linked to the appropriate sources with linkedTxomes and shared for computational reproducibility.

Maintained by Michael Love. Last updated 2 months ago.

annotation genomeannotation dataimport preprocessing rnaseq singlecell transcriptomics transcription geneexpression functionalgenomics reproducibleresearch reportwriting immunooncology

67 stars 10.54 score 466 scripts 1 dependents

bioc

ballgown:Flexible, isoform-level differential expression analysis

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

Maintained by Jack Fu. Last updated 5 months ago.

immunooncology rnaseq statisticalmethod preprocessing differentialexpression

145 stars 10.51 score 338 scripts 1 dependents

bioc

miloR:Differential neighbourhood abundance testing on a graph

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

Maintained by Mike Morgan. Last updated 5 months ago.

singlecell multiplecomparison functionalgenomics software openblas cpp openmp

362 stars 10.49 score 340 scripts 1 dependents

bioc

celda:CEllular Latent Dirichlet Allocation

Celda is a suite of Bayesian hierarchical models for clustering single-cell RNA-sequencing (scRNA-seq) data. It is able to perform "bi-clustering" and simultaneously cluster genes into gene modules and cells into cell subpopulations. It also contains DecontX, a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. A variety of scRNA-seq data visualization functions is also included.

Maintained by Joshua Campbell. Last updated 1 months ago.

singlecell geneexpression clustering sequencing bayesian immunooncology dataimport cpp openmp

147 stars 10.47 score 256 scripts 2 dependents

bioc

GENESIS:GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness

The GENESIS package provides methodology for estimating, inferring, and accounting for population and pedigree structure in genetic analyses. The current implementation provides functions to perform PC-AiR (Conomos et al., 2015, Gen Epi) and PC-Relate (Conomos et al., 2016, AJHG). PC-AiR performs a Principal Components Analysis on genome-wide SNP data for the detection of population structure in a sample that may contain known or cryptic relatedness. Unlike standard PCA, PC-AiR accounts for relatedness in the sample to provide accurate ancestry inference that is not confounded by family structure. PC-Relate uses ancestry representative principal components to adjust for population structure/ancestry and accurately estimate measures of recent genetic relatedness such as kinship coefficients, IBD sharing probabilities, and inbreeding coefficients. Additionally, functions are provided to perform efficient variance component estimation and mixed model association testing for both quantitative and binary phenotypes.

Maintained by Stephanie M. Gogarten. Last updated 2 months ago.

snp geneticvariability genetics statisticalmethod dimensionreduction principalcomponent genomewideassociation qualitycontrol biocviews

36 stars 10.44 score 342 scripts 1 dependents

bioc

oligo:Preprocessing tools for oligonucleotide arrays

A package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

Maintained by Benilton Carvalho. Last updated 24 days ago.

microarray onechannel twochannel preprocessing snp differentialexpression exonarray geneexpression dataimport zlib

3 stars 10.42 score 528 scripts 10 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 13 days ago.

software immunooncology singlecell classification annotation sequencing cpp

327 stars 10.42 score 240 scripts

egeulgen

pathfindR:Enrichment Analysis Utilizing Active Subnetworks

Enrichment analysis enables researchers to uncover mechanisms underlying a phenotype. However, conventional methods for enrichment analysis do not take into account protein-protein interaction information, resulting in incomplete conclusions. 'pathfindR' is a tool for enrichment analysis utilizing active subnetworks. The main function identifies active subnetworks in a protein-protein interaction network using a user-provided list of genes and associated p values. It then performs enrichment analyses on the identified subnetworks, identifying enriched terms (i.e. pathways or, more broadly, gene sets) that possibly underlie the phenotype of interest. 'pathfindR' also offers functionalities to cluster the enriched terms and identify representative terms in each cluster, to score the enriched terms per sample and to visualize analysis results. The enrichment, clustering and other methods implemented in 'pathfindR' are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2019. 'pathfindR': An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks. Front. Genet. <doi:10.3389/fgene.2019.00858>.

Maintained by Ege Ulgen. Last updated 1 months ago.

active-subnetworks enrichment pathway pathway-enrichment-analysis subnetwork

187 stars 10.38 score 138 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

pRoloc:A unifying bioinformatics framework for spatial proteomics

The pRoloc package implements machine learning and visualisation methods for the analysis and interogation of quantitiative mass spectrometry data to reliably infer protein sub-cellular localisation.

Maintained by Lisa Breckels. Last updated 5 days ago.

immunooncology proteomics massspectrometry classification clustering qualitycontrol bioconductor proteomics-data spatial-proteomics visualisation openblas cpp

15 stars 10.31 score 101 scripts 2 dependents

bioc

GSEABase:Gene set enrichment data structures and methods

This package provides classes and methods to support Gene Set Enrichment Analysis (GSEA).

Maintained by Bioconductor Package Maintainer. Last updated 2 months ago.

geneexpression genesetenrichment graphandnetwork go kegg

10.27 score 1.5k scripts 77 dependents

bioc

CAMERA:Collection of annotation related methods for mass spectrometry data

Annotation of peaklists generated by xcms, rule based annotation of isotopes and adducts, isotope validation, EIC correlation based tagging of unknown adducts and fragments

Maintained by Steffen Neumann. Last updated 5 months ago.

immunooncology massspectrometry metabolomics

11 stars 10.27 score 175 scripts 6 dependents

bioc

graphite:GRAPH Interaction from pathway Topological Environment

Graph objects from pathway topology derived from KEGG, Panther, PathBank, PharmGKB, Reactome SMPDB and WikiPathways databases.

Maintained by Gabriele Sales. Last updated 5 months ago.

pathways thirdpartyclient graphandnetwork network reactome kegg metabolomics bioinformatics mirror pathway-analysis

8 stars 10.24 score 122 scripts 21 dependents

bioc

EDASeq:Exploratory Data Analysis and Normalization for RNA-Seq

Numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010).

Maintained by Davide Risso. Last updated 5 months ago.

immunooncology sequencing rnaseq preprocessing qualitycontrol differentialexpression

5 stars 10.24 score 594 scripts 9 dependents

stemangiola

tidyHeatmap:A Tidy Implementation of Heatmap

This is a tidy implementation for heatmap. At the moment it is based on the (great) package 'ComplexHeatmap'. The goal of this package is to interface a tidy data frame with this powerful tool. Some of the advantages are: Row and/or columns colour annotations are easy to integrate just specifying one parameter (column names). Custom grouping of rows is easy to specify providing a grouped tbl. For example: df %>% group_by(...). Labels size adjusted by row and column total number. Default use of Brewer and Viridis palettes.

Maintained by Stefano Mangiola. Last updated 2 months ago.

assaydomain infrastructure brewer complexheatmap custom-palette dplyr graphviz heatmap mtcars plotting rstudio scale tibble tidy tidy-data-frame tidybulk tidyverse viridis

335 stars 10.23 score 197 scripts 1 dependents

bioc

UCell:Rank-based signature enrichment analysis for single-cell data

UCell is a package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory than other available methods, enabling the processing of large datasets in a few minutes even on machines with limited computing power. UCell can be applied to any single-cell data matrix, and includes functions to directly interact with SingleCellExperiment and Seurat objects.

Maintained by Massimo Andreatta. Last updated 5 months ago.

singlecell genesetenrichment transcriptomics geneexpression cellbasedassays

145 stars 10.21 score 454 scripts 2 dependents

bioc

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

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

Maintained by Davide Risso. Last updated 5 months ago.

immunooncology dimensionreduction geneexpression rnaseq software transcriptomics sequencing singlecell

43 stars 10.21 score 190 scripts 6 dependents

bioc

BiocIO:Standard Input and Output for Bioconductor Packages

The `BiocIO` package contains high-level abstract classes and generics used by developers to build IO funcionality within the Bioconductor suite of packages. Implements `import()` and `export()` standard generics for importing and exporting biological data formats. `import()` supports whole-file as well as chunk-wise iterative import. The `import()` interface optionally provides a standard mechanism for 'lazy' access via `filter()` (on row or element-like components of the file resource), `select()` (on column-like components of the file resource) and `collect()`. The `import()` interface optionally provides transparent access to remote (e.g. via https) as well as local access. Developers can register a file extension, e.g., `.loom` for dispatch from character-based URIs to specific `import()` / `export()` methods based on classes representing file types, e.g., `LoomFile()`.

Maintained by Marcel Ramos. Last updated 4 months ago.

annotation dataimport bioconductor-package core-package

1 stars 10.20 score 19 scripts 492 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 11 days ago.

software infrastructure thirdpartyclient bioconductor-package nci-itcr u24ca289073

33 stars 10.17 score 147 scripts 4 dependents

bioc

flowCore:flowCore: Basic structures for flow cytometry data

Provides S4 data structures and basic functions to deal with flow cytometry data.

Maintained by Mike Jiang. Last updated 5 months ago.

immunooncology infrastructure flowcytometry cellbasedassays cpp

10.17 score 1.7k scripts 59 dependents

bioc

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

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

Maintained by Joshua David Campbell. Last updated 1 months ago.

singlecell geneexpression differentialexpression alignment clustering immunooncology batcheffect normalization qualitycontrol dataimport gui

182 stars 10.17 score 252 scripts

bioc

plotgardener:Coordinate-Based Genomic Visualization Package for R

Coordinate-based genomic visualization package for R. It grants users the ability to programmatically produce complex, multi-paneled figures. Tailored for genomics, plotgardener allows users to visualize large complex genomic datasets and provides exquisite control over how plots are placed and arranged on a page.

Maintained by Nicole Kramer. Last updated 5 months ago.

visualization genomeannotation functionalgenomics genomeassembly hic cpp

309 stars 10.17 score 167 scripts 3 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

10.16 score 1.7k scripts 83 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

QDNAseq:Quantitative DNA Sequencing for Chromosomal Aberrations

Quantitative DNA sequencing for chromosomal aberrations. The genome is divided into non-overlapping fixed-sized bins, number of sequence reads in each counted, adjusted with a simultaneous two-dimensional loess correction for sequence mappability and GC content, and filtered to remove spurious regions in the genome. Downstream steps of segmentation and calling are also implemented via packages DNAcopy and CGHcall, respectively.

Maintained by Daoud Sie. Last updated 5 months ago.

copynumbervariation dnaseq genetics genomeannotation preprocessing qualitycontrol sequencing

49 stars 10.10 score 177 scripts 4 dependents

bioc

UCSC.utils:Low-level utilities to retrieve data from the UCSC Genome Browser

A set of low-level utilities to retrieve data from the UCSC Genome Browser. Most functions in the package access the data via the UCSC REST API but some of them query the UCSC MySQL server directly. Note that the primary purpose of the package is to support higher-level functionalities implemented in downstream packages like GenomeInfoDb or txdbmaker.

Maintained by Hervé Pagès. Last updated 3 months ago.

infrastructure genomeassembly annotation genomeannotation dataimport bioconductor-package core-package

1 stars 10.09 score 4 scripts 1.7k 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

sva:Surrogate Variable Analysis

The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data (like gene expression/RNA sequencing/methylation/brain imaging data) that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise. The sva package can be used to remove artifacts in three ways: (1) identifying and estimating surrogate variables for unknown sources of variation in high-throughput experiments (Leek and Storey 2007 PLoS Genetics,2008 PNAS), (2) directly removing known batch effects using ComBat (Johnson et al. 2007 Biostatistics) and (3) removing batch effects with known control probes (Leek 2014 biorXiv). Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008 PNAS or Leek et al. 2011 Nat. Reviews Genetics).

Maintained by Jeffrey T. Leek. Last updated 5 months ago.

immunooncology microarray statisticalmethod preprocessing multiplecomparison sequencing rnaseq batcheffect normalization

10.04 score 3.2k scripts 50 dependents

bioc

MOFA2:Multi-Omics Factor Analysis v2

The MOFA2 package contains a collection of tools for training and analysing multi-omic factor analysis (MOFA). MOFA is a probabilistic factor model that aims to identify principal axes of variation from data sets that can comprise multiple omic layers and/or groups of samples. Additional time or space information on the samples can be incorporated using the MEFISTO framework, which is part of MOFA2. Downstream analysis functions to inspect molecular features underlying each factor, vizualisation, imputation etc are available.

Maintained by Ricard Argelaguet. Last updated 5 months ago.

dimensionreduction bayesian visualization factor-analysis mofa multi-omics

326 stars 10.03 score 502 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

DropletUtils:Utilities for Handling Single-Cell Droplet Data

Provides a number of utility functions for handling single-cell (RNA-seq) data from droplet technologies such as 10X Genomics. This includes data loading from count matrices or molecule information files, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.

Maintained by Jonathan Griffiths. Last updated 4 months ago.

immunooncology singlecell sequencing rnaseq geneexpression transcriptomics dataimport coverage zlib cpp

10.01 score 2.7k scripts 9 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 19 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

methylumi:Handle Illumina methylation data

This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An "intelligent" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.

Maintained by Sean Davis. Last updated 5 months ago.

dnamethylation twochannel preprocessing qualitycontrol cpgisland

9 stars 9.90 score 89 scripts 9 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 2 days 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

GenVisR:Genomic Visualizations in R

Produce highly customizable publication quality graphics for genomic data primarily at the cohort level.

Maintained by Zachary Skidmore. Last updated 5 months ago.

infrastructure datarepresentation classification dnaseq

217 stars 9.87 score 76 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

RTCGAToolbox:A new tool for exporting TCGA Firehose data

Managing data from large scale projects such as The Cancer Genome Atlas (TCGA) for further analysis is an important and time consuming step for research projects. Several efforts, such as Firehose project, make TCGA pre-processed data publicly available via web services and data portals but it requires managing, downloading and preparing the data for following steps. We developed an open source and extensible R based data client for Firehose pre-processed data and demonstrated its use with sample case studies. Results showed that RTCGAToolbox could improve data management for researchers who are interested with TCGA data. In addition, it can be integrated with other analysis pipelines for following data analysis.

Maintained by Marcel Ramos. Last updated 3 months ago.

differentialexpression geneexpression sequencing

18 stars 9.75 score 76 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

rnabioco

valr:Genome Interval Arithmetic

Read and manipulate genome intervals and signals. Provides functionality similar to command-line tool suites within R, enabling interactive analysis and visualization of genome-scale data. Riemondy et al. (2017) <doi:10.12688/f1000research.11997.1>.

Maintained by Kent Riemondy. Last updated 23 days ago.

bedtools genome interval-arithmetic cpp

90 stars 9.69 score 227 scripts

bioc

txdbmaker:Tools for making TxDb objects from genomic annotations

A set of tools for making TxDb objects from genomic annotations from various sources (e.g. UCSC, Ensembl, and GFF files). These tools allow the user to download the genomic locations of transcripts, exons, and CDS, for a given assembly, and to import them in a TxDb object. TxDb objects are implemented in the GenomicFeatures package, together with flexible methods for extracting the desired features in convenient formats.

Maintained by H. Pagès. Last updated 4 months ago.

infrastructure dataimport annotation genomeannotation genomeassembly genetics sequencing bioconductor-package core-package

3 stars 9.68 score 92 scripts 87 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 4 months ago.

software workflowstep preprocessing dataimport bioconductor-package tcga u24ca289073 utilities

27 stars 9.66 score 210 scripts 10 dependents

plangfelder

WGCNA:Weighted Correlation Network Analysis

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.

Maintained by Peter Langfelder. Last updated 7 months ago.

cpp

54 stars 9.65 score 5.3k scripts 32 dependents

bioc

clustifyr:Classifier for Single-cell RNA-seq Using Cell Clusters

Package designed to aid in classifying cells from single-cell RNA sequencing data using external reference data (e.g., bulk RNA-seq, scRNA-seq, microarray, gene lists). A variety of correlation based methods and gene list enrichment methods are provided to assist cell type assignment.

Maintained by Rui Fu. Last updated 5 months ago.

singlecell annotation sequencing microarray geneexpression assign-identities clusters marker-genes rna-seq single-cell-rna-seq

120 stars 9.63 score 296 scripts

bioc

pcaExplorer:Interactive Visualization of RNA-seq Data Using a Principal Components Approach

This package provides functionality for interactive visualization of RNA-seq datasets based on Principal Components Analysis. The methods provided allow for quick information extraction and effective data exploration. A Shiny application encapsulates the whole analysis.

Maintained by Federico Marini. Last updated 3 months ago.

immunooncology visualization rnaseq dimensionreduction principalcomponent qualitycontrol gui reportwriting shinyapps bioconductor principal-components reproducible-research rna-seq-analysis rna-seq-data shiny transcriptome user-friendly

56 stars 9.63 score 180 scripts

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

AnnotationForge:Tools for building SQLite-based annotation data packages

Provides code for generating Annotation packages and their databases. Packages produced are intended to be used with AnnotationDbi.

Maintained by Bioconductor Package Maintainer. Last updated 19 days ago.

annotation infrastructure bioconductor-package core-package

5 stars 9.62 score 143 scripts 19 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

tidybulk:Brings transcriptomics to the tidyverse

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

Maintained by Stefano Mangiola. Last updated 15 days ago.

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

171 stars 9.57 score 172 scripts 1 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

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

DEGreport:Report of DEG analysis

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

Maintained by Lorena Pantano. Last updated 5 months ago.

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

24 stars 9.42 score 354 scripts 1 dependents

bioc

MetaboCoreUtils:Core Utils for Metabolomics Data

MetaboCoreUtils defines metabolomics-related core functionality provided as low-level functions to allow a data structure-independent usage across various R packages. This includes functions to calculate between ion (adduct) and compound mass-to-charge ratios and masses or functions to work with chemical formulas. The package provides also a set of adduct definitions and information on some commercially available internal standard mixes commonly used in MS experiments.

Maintained by Johannes Rainer. Last updated 5 months ago.

infrastructure metabolomics massspectrometry mass-spectrometry

9 stars 9.40 score 58 scripts 36 dependents

bioc

SpatialFeatureExperiment:Integrating SpatialExperiment with Simple Features in sf

A new S4 class integrating Simple Features with the R package sf to bring geospatial data analysis methods based on vector data to spatial transcriptomics. Also implements management of spatial neighborhood graphs and geometric operations. This pakage builds upon SpatialExperiment and SingleCellExperiment, hence methods for these parent classes can still be used.

Maintained by Lambda Moses. Last updated 2 months ago.

datarepresentation transcriptomics spatial

49 stars 9.40 score 322 scripts 1 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

LOLA:Locus overlap analysis for enrichment of genomic ranges

Provides functions for testing overlap of sets of genomic regions with public and custom region set (genomic ranges) databases. This makes it possible to do automated enrichment analysis for genomic region sets, thus facilitating interpretation of functional genomics and epigenomics data.

Maintained by Nathan Sheffield. Last updated 5 months ago.

genesetenrichment generegulation genomeannotation systemsbiology functionalgenomics chipseq methylseq sequencing

76 stars 9.34 score 160 scripts

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

EWCE:Expression Weighted Celltype Enrichment

Used to determine which cell types are enriched within gene lists. The package provides tools for testing enrichments within simple gene lists (such as human disease associated genes) and those resulting from differential expression studies. The package does not depend upon any particular Single Cell Transcriptome dataset and user defined datasets can be loaded in and used in the analyses.

Maintained by Alan Murphy. Last updated 2 months ago.

geneexpression transcription differentialexpression genesetenrichment genetics microarray mrnamicroarray onechannel rnaseq biomedicalinformatics proteomics visualization functionalgenomics singlecell deconvolution single-cell single-cell-rna-seq transcriptomics

56 stars 9.29 score 99 scripts

bioc

CNEr:CNE Detection and Visualization

Large-scale identification and advanced visualization of sets of conserved noncoding elements.

Maintained by Ge Tan. Last updated 5 months ago.

generegulation visualization dataimport

3 stars 9.28 score 35 scripts 19 dependents

bioc

IsoformSwitchAnalyzeR:Identify, Annotate and Visualize Isoform Switches with Functional Consequences from both short- and long-read RNA-seq data

Analysis of alternative splicing and isoform switches with predicted functional consequences (e.g. gain/loss of protein domains etc.) from quantification of all types of RNASeq by tools such as Kallisto, Salmon, StringTie, Cufflinks/Cuffdiff etc.

Maintained by Kristoffer Vitting-Seerup. Last updated 5 months ago.

geneexpression transcription alternativesplicing differentialexpression differentialsplicing visualization statisticalmethod transcriptomevariant biomedicalinformatics functionalgenomics systemsbiology transcriptomics rnaseq annotation functionalprediction geneprediction dataimport multiplecomparison batcheffect immunooncology

108 stars 9.26 score 125 scripts

bioc

RcisTarget:RcisTarget Identify transcription factor binding motifs enriched on a list of genes or genomic regions

RcisTarget identifies transcription factor binding motifs (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the transcription start site (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high Normalized Enrichment Score (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).

Maintained by Gert Hulselmans. Last updated 5 months ago.

generegulation motifannotation transcriptomics transcription genesetenrichment genetarget

37 stars 9.18 score 191 scripts

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 19 days ago.

sequencing rnaseq software geneexpression transcriptomics singlecell batcheffect normalization cpp

9.10 score 1.2k scripts 10 dependents

bioc

sesame:SEnsible Step-wise Analysis of DNA MEthylation BeadChips

Tools For analyzing Illumina Infinium DNA methylation arrays. SeSAMe provides utilities to support analyses of multiple generations of Infinium DNA methylation BeadChips, including preprocessing, quality control, visualization and inference. SeSAMe features accurate detection calling, intelligent inference of ethnicity, sex and advanced quality control routines.

Maintained by Wanding Zhou. Last updated 3 months ago.

dnamethylation methylationarray preprocessing qualitycontrol bioinformatics dna-methylation microarray

69 stars 9.08 score 258 scripts 1 dependents

bioc

OUTRIDER:OUTRIDER - OUTlier in RNA-Seq fInDER

Identification of aberrant gene expression in RNA-seq data. Read count expectations are modeled by an autoencoder to control for confounders in the data. Given these expectations, the RNA-seq read counts are assumed to follow a negative binomial distribution with a gene-specific dispersion. Outliers are then identified as read counts that significantly deviate from this distribution. Furthermore, OUTRIDER provides useful plotting functions to analyze and visualize the results.

Maintained by Christian Mertes. Last updated 5 months ago.

immunooncology rnaseq transcriptomics alignment sequencing geneexpression genetics count-data diagnostics expression-analysis mendelian-genetics outlier-detection rna-seq openblas cpp

50 stars 9.07 score 110 scripts 1 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 14 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

Banksy:Spatial transcriptomic clustering

Banksy is an R package that incorporates spatial information to cluster cells in a feature space (e.g. gene expression). To incorporate spatial information, BANKSY computes the mean neighborhood expression and azimuthal Gabor filters that capture gene expression gradients. These features are combined with the cell's own expression to embed cells in a neighbor-augmented product space which can then be clustered, allowing for accurate and spatially-aware cell typing and tissue domain segmentation.

Maintained by Joseph Lee. Last updated 28 days ago.

clustering spatial singlecell geneexpression dimensionreduction clustering-algorithm single-cell-omics spatial-omics

90 stars 9.03 score 248 scripts

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 4 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

regioneR:Association analysis of genomic regions based on permutation tests

regioneR offers a statistical framework based on customizable permutation tests to assess the association between genomic region sets and other genomic features.

Maintained by Bernat Gel. Last updated 5 months ago.

genetics chipseq dnaseq methylseq copynumbervariation

9.01 score 2.7k scripts 21 dependents

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

topGO:Enrichment Analysis for Gene Ontology

topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.

Maintained by Adrian Alexa. Last updated 5 months ago.

microarray visualization

8.96 score 2.0k scripts 20 dependents

bioc

bamsignals:Extract read count signals from bam files

This package allows to efficiently obtain count vectors from indexed bam files. It counts the number of reads in given genomic ranges and it computes reads profiles and coverage profiles. It also handles paired-end data.

Maintained by Johannes Helmuth. Last updated 5 months ago.

dataimport sequencing coverage alignment curl bzip2 xz-utils zlib cpp

15 stars 8.95 score 31 scripts 11 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 1 months ago.

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

26 stars 8.95 score 115 scripts

bioc

RaggedExperiment:Representation of Sparse Experiments and Assays Across Samples

This package provides a flexible representation of copy number, mutation, and other data that fit into the ragged array schema for genomic location data. The basic representation of such data provides a rectangular flat table interface to the user with range information in the rows and samples/specimen in the columns. The RaggedExperiment class derives from a GRangesList representation and provides a semblance of a rectangular dataset.

Maintained by Marcel Ramos. Last updated 4 months ago.

infrastructure datarepresentation copynumber core-package data-structure mutations u24ca289073

4 stars 8.93 score 76 scripts 14 dependents

bioc

motifbreakR:A Package For Predicting The Disruptiveness Of Single Nucleotide Polymorphisms On Transcription Factor Binding Sites

We introduce motifbreakR, which allows the biologist to judge in the first place whether the sequence surrounding the polymorphism is a good match, and in the second place how much information is gained or lost in one allele of the polymorphism relative to another. MotifbreakR is both flexible and extensible over previous offerings; giving a choice of algorithms for interrogation of genomes with motifs from public sources that users can choose from; these are 1) a weighted-sum probability matrix, 2) log-probabilities, and 3) weighted by relative entropy. MotifbreakR can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within Bioconductor (currently there are 32 species, a total of 109 versions).

Maintained by Simon Gert Coetzee. Last updated 5 months ago.

chipseq visualization motifannotation transcription

28 stars 8.89 score 103 scripts

bioc

tidySingleCellExperiment:Brings SingleCellExperiment to the Tidyverse

'tidySingleCellExperiment' is an adapter that abstracts the 'SingleCellExperiment' container in the form of a 'tibble'. This allows *tidy* data manipulation, nesting, and plotting. For example, a 'tidySingleCellExperiment' is directly compatible with functions from 'tidyverse' packages `dplyr` and `tidyr`, as well as plotting with `ggplot2` and `plotly`. In addition, the package provides various utility functions specific to single-cell omics data analysis (e.g., aggregation of cell-level data to pseudobulks).

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression singlecell geneexpression normalization clustering qualitycontrol sequencing bioconductor dplyr ggplot2 plotly single-cell-rna-seq single-cell-sequencing singlecellexperiment tibble tidyr tidyverse

36 stars 8.86 score 125 scripts 2 dependents

bioc

cmapR:CMap Tools in R

The Connectivity Map (CMap) is a massive resource of perturbational gene expression profiles built by researchers at the Broad Institute and funded by the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. Please visit https://clue.io for more information. The cmapR package implements methods to parse, manipulate, and write common CMap data objects, such as annotated matrices and collections of gene sets.

Maintained by Ted Natoli. Last updated 5 months ago.

dataimport datarepresentation geneexpression bioconductor bioinformatics cmap

90 stars 8.86 score 298 scripts

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

SeqVarTools:Tools for variant data

An interface to the fast-access storage format for VCF data provided in SeqArray, with tools for common operations and analysis.

Maintained by Stephanie M. Gogarten. Last updated 5 months ago.

snp geneticvariability sequencing genetics

3 stars 8.76 score 384 scripts 2 dependents

bioc

ChIPpeakAnno:Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments, or any experiments that result in large number of genomic interval data

The package encompasses a range of functions for identifying the closest gene, exon, miRNA, or custom features—such as highly conserved elements and user-supplied transcription factor binding sites. Additionally, users can retrieve sequences around the peaks and obtain enriched Gene Ontology (GO) or Pathway terms. In version 2.0.5 and beyond, new functionalities have been introduced. These include features for identifying peaks associated with bi-directional promoters along with summary statistics (peaksNearBDP), summarizing motif occurrences in peaks (summarizePatternInPeaks), and associating additional identifiers with annotated peaks or enrichedGO (addGeneIDs). The package integrates with various other packages such as biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest, and stat to enhance its analytical capabilities.

Maintained by Jianhong Ou. Last updated 3 months ago.

annotation chipseq chipchip

8.75 score 584 scripts 6 dependents

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 4 days ago.

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

3 stars 8.72 score 20 scripts 3 dependents

bioc

GenomicScores:Infrastructure to work with genomewide position-specific scores

Provide infrastructure to store and access genomewide position-specific scores within R and Bioconductor.

Maintained by Robert Castelo. Last updated 2 months ago.

infrastructure genetics annotation sequencing coverage annotationhubsoftware

8 stars 8.71 score 83 scripts 6 dependents

bioc

Voyager:From geospatial to spatial omics

SpatialFeatureExperiment (SFE) is a new S4 class for working with spatial single-cell genomics data. The voyager package implements basic exploratory spatial data analysis (ESDA) methods for SFE. Univariate methods include univariate global spatial ESDA methods such as Moran's I, permutation testing for Moran's I, and correlograms. Bivariate methods include Lee's L and cross variogram. Multivariate methods include MULTISPATI PCA and multivariate local Geary's C recently developed by Anselin. The Voyager package also implements plotting functions to plot SFE data and ESDA results.

Maintained by Lambda Moses. Last updated 3 months ago.

geneexpression spatial transcriptomics visualization bioconductor eda esda exploratory-data-analysis omics spatial-statistics spatial-transcriptomics

88 stars 8.71 score 173 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

trackViewer:A R/Bioconductor package with web interface for drawing elegant interactive tracks or lollipop plot to facilitate integrated analysis of multi-omics data

Visualize mapped reads along with annotation as track layers for NGS dataset such as ChIP-seq, RNA-seq, miRNA-seq, DNA-seq, SNPs and methylation data.

Maintained by Jianhong Ou. Last updated 5 days ago.

visualization

8.68 score 145 scripts 2 dependents

bioc

gage:Generally Applicable Gene-set Enrichment for Pathway Analysis

GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.

Maintained by Weijun Luo. Last updated 5 months ago.

pathways go differentialexpression microarray onechannel twochannel rnaseq genetics multiplecomparison genesetenrichment geneexpression systemsbiology sequencing

5 stars 8.68 score 784 scripts 1 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 13 days ago.

microbiome software visualization bioconductor microbiome-analysis plotting

10 stars 8.67 score 81 scripts 1 dependents

bioc

apeglm:Approximate posterior estimation for GLM coefficients

apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.

Maintained by Anqi Zhu. Last updated 5 months ago.

immunooncology sequencing rnaseq differentialexpression geneexpression bayesian cpp

8.65 score 700 scripts 9 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

QuasR:Quantify and Annotate Short Reads in R

This package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest. Read alignments are either generated through Rbowtie (data from DNA/ChIP/ATAC/Bis-seq experiments) or Rhisat2 (data from RNA-seq experiments that require spliced alignments), or can be provided in the form of bam files.

Maintained by Michael Stadler. Last updated 1 months ago.

genetics preprocessing sequencing chipseq rnaseq methylseq coverage alignment qualitycontrol immunooncology curl bzip2 xz-utils zlib cpp

6 stars 8.63 score 79 scripts 1 dependents

bioc

AUCell:AUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)

AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched within the expressed genes for each cell. The distribution of AUC scores across all the cells allows exploring the relative expression of the signature. Since the scoring method is ranking-based, AUCell is independent of the gene expression units and the normalization procedure. In addition, since the cells are evaluated individually, it can easily be applied to bigger datasets, subsetting the expression matrix if needed.

Maintained by Gert Hulselmans. Last updated 5 months ago.

singlecell genesetenrichment transcriptomics transcription geneexpression workflowstep normalization

8.59 score 860 scripts 4 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 17 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

44 stars 8.53 score 155 scripts

bioc

MsExperiment:Infrastructure for Mass Spectrometry Experiments

Infrastructure to store and manage all aspects related to a complete proteomics or metabolomics mass spectrometry (MS) experiment. The MsExperiment package provides light-weight and flexible containers for MS experiments building on the new MS infrastructure provided by the Spectra, QFeatures and related packages. Along with raw data representations, links to original data files and sample annotations, additional metadata or annotations can also be stored within the MsExperiment container. To guarantee maximum flexibility only minimal constraints are put on the type and content of the data within the containers.

Maintained by Laurent Gatto. Last updated 2 months ago.

infrastructure proteomics massspectrometry metabolomics experimentaldesign dataimport

5 stars 8.51 score 126 scripts 14 dependents

bioc

ReactomeGSA:Client for the Reactome Analysis Service for comparative multi-omics gene set analysis

The ReactomeGSA packages uses Reactome's online analysis service to perform a multi-omics gene set analysis. The main advantage of this package is, that the retrieved results can be visualized using REACTOME's powerful webapplication. Since Reactome's analysis service also uses R to perfrom the actual gene set analysis you will get similar results when using the same packages (such as limma and edgeR) locally. Therefore, if you only require a gene set analysis, different packages are more suited.

Maintained by Johannes Griss. Last updated 4 months ago.

genesetenrichment proteomics transcriptomics systemsbiology geneexpression reactome

22 stars 8.50 score 67 scripts 1 dependents