R-universe search: needs:Rhdf5lib

bioc

rhdf5:R Interface to HDF5

This package provides an interface between HDF5 and R. HDF5's main features are the ability to store and access very large and/or complex datasets and a wide variety of metadata on mass storage (disk) through a completely portable file format. The rhdf5 package is thus suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM.

Maintained by Mike Smith. Last updated 5 days ago.

infrastructure dataimport hdf5 rhdf5 openssl curl zlib cpp

62 stars 15.87 score 4.2k scripts 232 dependents

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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 9 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

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 16 days ago.

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

196 stars 14.31 score 984 scripts 11 dependents

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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

597 stars 13.90 score 8.4k scripts 37 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 10 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

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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

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mzR:parser for netCDF, mzXML and mzML and mzIdentML files (mass spectrometry data)

mzR provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a subset of the proteowizard library for mzXML, mzML and mzIdentML. The netCDF reading code has previously been used in XCMS.

Maintained by Steffen Neumann. Last updated 2 months ago.

immunooncology infrastructure dataimport proteomics metabolomics massspectrometry zlib cpp

45 stars 12.77 score 204 scripts 44 dependents

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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 15 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

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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

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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 3 months ago.

dnamethylation cpp

37 stars 12.26 score 676 scripts 15 dependents

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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 13 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

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biomformat:An interface package for the BIOM file format

This is an R package for interfacing with the BIOM format. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object (which is more complex than a single table), as well as limited support for writing a biom-object back to a biom-format file. The design of this API is intended to match the python API and other tools included with the biom-format project, but with a decidedly "R flavor" that should be familiar to R users. This includes S4 classes and methods, as well as extensions of common core functions/methods.

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

immunooncology dataimport metagenomics microbiome

7 stars 11.39 score 416 scripts 40 dependents

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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

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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

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 2 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

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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

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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

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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

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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

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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

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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

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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

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rhdf5filters:HDF5 Compression Filters

Provides a collection of additional compression filters for HDF5 datasets. The package is intended to provide seemless integration with rhdf5, however the compiled filters can also be used with external applications.

Maintained by Mike Smith. Last updated 5 days ago.

infrastructure dataimport compression filter-plugin hdf5

5 stars 9.90 score 4 scripts 233 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

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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 1 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

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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

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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

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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

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

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

Maintained by Shian Su. Last updated 3 months ago.

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

68 stars 9.02 score 84 scripts

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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

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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

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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

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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

adokter

bioRad:Biological Analysis and Visualization of Weather Radar Data

Extract, visualize and summarize aerial movements of birds and insects from weather radar data. See Dokter, A. M. et al. (2018) "bioRad: biological analysis and visualization of weather radar data" <doi:10.1111/ecog.04028> for a software paper describing package and methodologies.

Maintained by Adriaan M. Dokter. Last updated 4 days ago.

aeroecology enram eumetnet-opera lifewatch movement-ecology nexrad oscibio radar weather-radar wsr-88d

29 stars 8.70 score 56 scripts

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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 3 days ago.

visualization

8.68 score 145 scripts 2 dependents

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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

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FRASER:Find RAre Splicing Events in RNA-Seq Data

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

Maintained by Christian Mertes. Last updated 5 months ago.

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

41 stars 8.50 score 155 scripts

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alabaster.base:Save Bioconductor Objects to File

Save Bioconductor data structures into file artifacts, and load them back into memory. This is a more robust and portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

Maintained by Aaron Lun. Last updated 25 days ago.

datarepresentation dataimport zlib cpp

3 stars 8.47 score 60 scripts 15 dependents

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

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

Maintained by Julien Wollbrett. Last updated 5 months ago.

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

15 stars 8.46 score 19 scripts 1 dependents

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flowStats:Statistical methods for the analysis of flow cytometry data

Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package.

Maintained by Greg Finak. Last updated 5 months ago.

immunooncology flowcytometry cellbasedassays

14 stars 8.27 score 195 scripts 1 dependents

adw96

breakaway:Species Richness Estimation and Modeling

Understanding the drivers of microbial diversity is an important frontier of microbial ecology, and investigating the diversity of samples from microbial ecosystems is a common step in any microbiome analysis. 'breakaway' is the premier package for statistical analysis of microbial diversity. 'breakaway' implements the latest and greatest estimates of species richness, described in Willis and Bunge (2015) <doi:10.1111/biom.12332>, Willis et al. (2017) <doi:10.1111/rssc.12206>, and Willis (2016) <arXiv:1604.02598>, as well as the most commonly used estimates, including the objective Bayes approach described in Barger and Bunge (2010) <doi:10.1214/10-BA527>.

Maintained by Amy D Willis. Last updated 1 years ago.

68 stars 8.18 score 211 scripts

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IPO:Automated Optimization of XCMS Data Processing parameters

The outcome of XCMS data processing strongly depends on the parameter settings. IPO (`Isotopologue Parameter Optimization`) is a parameter optimization tool that is applicable for different kinds of samples and liquid chromatography coupled to high resolution mass spectrometry devices, fast and free of labeling steps. IPO uses natural, stable 13C isotopes to calculate a peak picking score. Retention time correction is optimized by minimizing the relative retention time differences within features and grouping parameters are optimized by maximizing the number of features showing exactly one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiment. The resulting scores are evaluated using response surface models.

Maintained by Thomas Lieb. Last updated 5 months ago.

immunooncology metabolomics massspectrometry

34 stars 8.14 score 41 scripts

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openCyto:Hierarchical Gating Pipeline for flow cytometry data

This package is designed to facilitate the automated gating methods in sequential way to mimic the manual gating strategy.

Maintained by Mike Jiang. Last updated 3 days ago.

immunooncology flowcytometry dataimport preprocessing datarepresentation cpp

8.02 score 404 scripts 1 dependents

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spicyR:Spatial analysis of in situ cytometry data

The spicyR package provides a framework for performing inference on changes in spatial relationships between pairs of cell types for cell-resolution spatial omics technologies. spicyR consists of three primary steps: (i) summarizing the degree of spatial localization between pairs of cell types for each image; (ii) modelling the variability in localization summary statistics as a function of cell counts and (iii) testing for changes in spatial localizations associated with a response variable.

Maintained by Ellis Patrick. Last updated 25 days ago.

singlecell cellbasedassays spatial

9 stars 8.02 score 57 scripts 1 dependents

bioc

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

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

Maintained by Tara Eicher. Last updated 11 days ago.

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

105 stars 7.98 score

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FLAMES:FLAMES: Full Length Analysis of Mutations and Splicing in long read RNA-seq data

Semi-supervised isoform detection and annotation from both bulk and single-cell long read RNA-seq data. Flames provides automated pipelines for analysing isoforms, as well as intermediate functions for manual execution.

Maintained by Changqing Wang. Last updated 19 days ago.

rnaseq singlecell transcriptomics dataimport differentialsplicing alternativesplicing geneexpression longread zlib curl bzip2 xz-utils cpp

31 stars 7.95 score 12 scripts

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BayesSpace:Clustering and Resolution Enhancement of Spatial Transcriptomes

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

Maintained by Matt Stone. Last updated 5 months ago.

software clustering transcriptomics geneexpression singlecell immunooncology dataimport openblas cpp openmp

126 stars 7.90 score 278 scripts 1 dependents

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flowWorkspace:Infrastructure for representing and interacting with gated and ungated cytometry data sets.

This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.

Maintained by Greg Finak. Last updated 23 days ago.

immunooncology flowcytometry dataimport preprocessing datarepresentation zlib openblas cpp

7.89 score 576 scripts 10 dependents

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wateRmelon:Illumina DNA methylation array normalization and metrics

15 flavours of betas and three performance metrics, with methods for objects produced by methylumi and minfi packages.

Maintained by Leo C Schalkwyk. Last updated 4 months ago.

dnamethylation microarray twochannel preprocessing qualitycontrol

7.75 score 247 scripts 2 dependents

bioc

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

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

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

cellbiology flowcytometry clustering visualization software cellbasedassays

7.71 score 468 scripts 10 dependents

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lemur:Latent Embedding Multivariate Regression

Fit a latent embedding multivariate regression (LEMUR) model to multi-condition single-cell data. The model provides a parametric description of single-cell data measured with treatment vs. control or more complex experimental designs. The parametric model is used to (1) align conditions, (2) predict log fold changes between conditions for all cells, and (3) identify cell neighborhoods with consistent log fold changes. For those neighborhoods, a pseudobulked differential expression test is conducted to assess which genes are significantly changed.

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

transcriptomics differentialexpression singlecell dimensionreduction regression openblas cpp

87 stars 7.69 score 81 scripts

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phantasus:Visual and interactive gene expression analysis

Phantasus is a web-application for visual and interactive gene expression analysis. Phantasus is based on Morpheus – a web-based software for heatmap visualisation and analysis, which was integrated with an R environment via OpenCPU API. Aside from basic visualization and filtering methods, R-based methods such as k-means clustering, principal component analysis or differential expression analysis with limma package are supported.

Maintained by Alexey Sergushichev. Last updated 5 months ago.

geneexpression gui visualization datarepresentation transcriptomics rnaseq microarray normalization clustering differentialexpression principalcomponent immunooncology

43 stars 7.68 score 15 scripts

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CytoML:A GatingML Interface for Cross Platform Cytometry Data Sharing

Uses platform-specific implemenations of the GatingML2.0 standard to exchange gated cytometry data with other software platforms.

Maintained by Mike Jiang. Last updated 23 days ago.

immunooncology flowcytometry dataimport datarepresentation zlib openblas libxml2 cpp

30 stars 7.60 score 132 scripts

bioc

imcRtools:Methods for imaging mass cytometry data analysis

This R package supports the handling and analysis of imaging mass cytometry and other highly multiplexed imaging data. The main functionality includes reading in single-cell data after image segmentation and measurement, data formatting to perform channel spillover correction and a number of spatial analysis approaches. First, cell-cell interactions are detected via spatial graph construction; these graphs can be visualized with cells representing nodes and interactions representing edges. Furthermore, per cell, its direct neighbours are summarized to allow spatial clustering. Per image/grouping level, interactions between types of cells are counted, averaged and compared against random permutations. In that way, types of cells that interact more (attraction) or less (avoidance) frequently than expected by chance are detected.

Maintained by Daniel Schulz. Last updated 5 months ago.

immunooncology singlecell spatial dataimport clustering imc single-cell

24 stars 7.58 score 126 scripts

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ncdfFlow:ncdfFlow: A package that provides HDF5 based storage for flow cytometry data.

Provides HDF5 storage based methods and functions for manipulation of flow cytometry data.

Maintained by Mike Jiang. Last updated 3 months ago.

immunooncology flowcytometry zlib cpp

7.56 score 96 scripts 11 dependents

bioc

MIRA:Methylation-Based Inference of Regulatory Activity

DNA methylation contains information about the regulatory state of the cell. MIRA aggregates genome-scale DNA methylation data into a DNA methylation profile for a given region set with shared biological annotation. Using this profile, MIRA infers and scores the collective regulatory activity for the region set. MIRA facilitates regulatory analysis in situations where classical regulatory assays would be difficult and allows public sources of region sets to be leveraged for novel insight into the regulatory state of DNA methylation datasets.

Maintained by John Lawson. Last updated 5 months ago.

immunooncology dnamethylation generegulation genomeannotation systemsbiology functionalgenomics chipseq methylseq sequencing epigenetics coverage

12 stars 7.56 score 7 scripts 1 dependents

bioc

methrix:Fast and efficient summarization of generic bedGraph files from Bisufite sequencing

Bedgraph files generated by Bisulfite pipelines often come in various flavors. Critical downstream step requires summarization of these files into methylation/coverage matrices. This step of data aggregation is done by Methrix, including many other useful downstream functions.

Maintained by Anand Mayakonda. Last updated 5 months ago.

dnamethylation sequencing coverage bedgraph bioinformatics dna-methylation

32 stars 7.53 score 39 scripts 1 dependents

bioc

metaMS:MS-based metabolomics annotation pipeline

MS-based metabolomics data processing and compound annotation pipeline.

Maintained by Yann Guitton. Last updated 5 months ago.

immunooncology massspectrometry metabolomics

15 stars 7.50 score 15 scripts

bioc

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

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

Maintained by Alexander Dietrich. Last updated 2 days ago.

software rnaseq singlecell

15 stars 7.50 score 29 scripts 1 dependents

bioc

flowViz:Visualization for flow cytometry

Provides visualization tools for flow cytometry data.

Maintained by Mike Jiang. Last updated 5 months ago.

immunooncology infrastructure flowcytometry cellbasedassays visualization

7.44 score 231 scripts 12 dependents

bioc

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

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

Maintained by Davide Risso. Last updated 5 months ago.

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

10 stars 7.41 score 54 scripts 2 dependents

bioc

netSmooth:Network smoothing for scRNAseq

netSmooth is an R package for network smoothing of single cell RNA sequencing data. Using bio networks such as protein-protein interactions as priors for gene co-expression, netsmooth improves cell type identification from noisy, sparse scRNAseq data.

Maintained by Jonathan Ronen. Last updated 5 months ago.

network graphandnetwork singlecell rnaseq geneexpression sequencing transcriptomics normalization preprocessing clustering dimensionreduction bioinformatics genomics single-cell

27 stars 7.41 score 4 scripts

bioc

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

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

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

dnamethylation differentialmethylation epigenetics regression methylseq differential-methylation dna-methylation

18 stars 7.40 score 23 scripts

bioc

cytolib:C++ infrastructure for representing and interacting with the gated cytometry data

This package provides the core data structure and API to represent and interact with the gated cytometry data.

Maintained by Mike Jiang. Last updated 2 months ago.

immunooncology flowcytometry dataimport preprocessing datarepresentation

7.39 score 7 scripts 60 dependents

bioc

PeacoQC:Peak-based selection of high quality cytometry data

This is a package that includes pre-processing and quality control functions that can remove margin events, compensate and transform the data and that will use PeacoQCSignalStability for quality control. This last function will first detect peaks in each channel of the flowframe. It will remove anomalies based on the IsolationTree function and the MAD outlier detection method. This package can be used for both flow- and mass cytometry data.

Maintained by Annelies Emmaneel. Last updated 5 months ago.

flowcytometry qualitycontrol preprocessing peakdetection

16 stars 7.38 score 28 scripts 3 dependents

bioc

shinyMethyl:Interactive visualization for Illumina methylation arrays

Interactive tool for visualizing Illumina methylation array data. Both the 450k and EPIC array are supported.

Maintained by Jean-Philippe Fortin. Last updated 5 months ago.

dnamethylation microarray twochannel preprocessing qualitycontrol methylationarray

5 stars 7.34 score 42 scripts

bioc

flowClust:Clustering for Flow Cytometry

Robust model-based clustering using a t-mixture model with Box-Cox transformation. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'.

Maintained by Greg Finak. Last updated 5 months ago.

immunooncology clustering visualization flowcytometry

7.31 score 83 scripts 6 dependents

bioc

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

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

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing normalization

9 stars 7.30 score 37 scripts 2 dependents

waldronlab

SingleCellMultiModal:Integrating Multi-modal Single Cell Experiment datasets

SingleCellMultiModal is an ExperimentHub package that serves multiple datasets obtained from GEO and other sources and represents them as MultiAssayExperiment objects. We provide several multi-modal datasets including scNMT, 10X Multiome, seqFISH, CITEseq, SCoPE2, and others. The scope of the package is is to provide data for benchmarking and analysis. To cite, use the 'citation' function and see <https://doi.org/10.1371/journal.pcbi.1011324>.

Maintained by Marcel Ramos. Last updated 4 months ago.

experimentdata singlecelldata reproducibleresearch experimenthub geo bioconductor-package u24ca289073

17 stars 7.29 score 60 scripts

bioc

TBSignatureProfiler:Profile RNA-Seq Data Using TB Pathway Signatures

Gene signatures of TB progression, TB disease, and other TB disease states have been validated and published previously. This package aggregates known signatures and provides computational tools to enlist their usage on other datasets. The TBSignatureProfiler makes it easy to profile RNA-Seq data using these signatures and includes common signature profiling tools including ASSIGN, GSVA, and ssGSEA. Original models for some gene signatures are also available. A shiny app provides some functionality alongside for detailed command line accessibility.

Maintained by Aubrey R. Odom. Last updated 3 months ago.

geneexpression differentialexpression bioconductor-package biomarkers gene-signatures tuberculosis

12 stars 7.25 score 23 scripts

bioc

missMethyl:Analysing Illumina HumanMethylation BeadChip Data

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

Maintained by Belinda Phipson. Last updated 27 days ago.

normalization dnamethylation methylationarray genomicvariation geneticvariability differentialmethylation genesetenrichment

7.24 score 300 scripts 1 dependents

bioc

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

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

Maintained by Timothy Keyes. Last updated 5 months ago.

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

18 stars 7.24 score 35 scripts

bioc

CRISPRseek:Design of guide RNAs in CRISPR genome-editing systems

The package encompasses functions to find potential guide RNAs for the CRISPR-based genome-editing systems including the Base Editors and the Prime Editors when supplied with target sequences as input. Users have the flexibility to filter resulting guide RNAs based on parameters such as the absence of restriction enzyme cut sites or the lack of paired guide RNAs. The package also facilitates genome-wide exploration for off-targets, offering features to score and rank off-targets, retrieve flanking sequences, and indicate whether the hits are located within exon regions. All detected guide RNAs are annotated with the cumulative scores of the top5 and topN off-targets together with the detailed information such as mismatch sites and restrictuion enzyme cut sites. The package also outputs INDELs and their frequencies for Cas9 targeted sites.

Maintained by Lihua Julie Zhu. Last updated 19 days ago.

immunooncology generegulation sequencematching crispr

7.18 score 51 scripts 2 dependents

bioc

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

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

Maintained by Brendan Gongol. Last updated 5 months ago.

software geneexpression go kegg networkenrichment sequencing coverage differentialexpression cpp

17 stars 7.18 score 74 scripts 1 dependents

bioc

SPsimSeq:Semi-parametric simulation tool for bulk and single-cell RNA sequencing data

SPsimSeq uses a specially designed exponential family for density estimation to constructs the distribution of gene expression levels from a given real RNA sequencing data (single-cell or bulk), and subsequently simulates a new dataset from the estimated marginal distributions using Gaussian-copulas to retain the dependence between genes. It allows simulation of multiple groups and batches with any required sample size and library size.

Maintained by Joris Meys. Last updated 5 months ago.

geneexpression rnaseq singlecell sequencing dnaseq

10 stars 7.14 score 29 scripts 1 dependents

bioc

ATACseqQC:ATAC-seq Quality Control

ATAC-seq, an assay for Transposase-Accessible Chromatin using sequencing, is a rapid and sensitive method for chromatin accessibility analysis. It was developed as an alternative method to MNase-seq, FAIRE-seq and DNAse-seq. Comparing to the other methods, ATAC-seq requires less amount of the biological samples and time to process. In the process of analyzing several ATAC-seq dataset produced in our labs, we learned some of the unique aspects of the quality assessment for ATAC-seq data.To help users to quickly assess whether their ATAC-seq experiment is successful, we developed ATACseqQC package partially following the guideline published in Nature Method 2013 (Greenleaf et al.), including diagnostic plot of fragment size distribution, proportion of mitochondria reads, nucleosome positioning pattern, and CTCF or other Transcript Factor footprints.

Maintained by Jianhong Ou. Last updated 3 months ago.

sequencing dnaseq atacseq generegulation qualitycontrol coverage nucleosomepositioning immunooncology

7.12 score 146 scripts 1 dependents

bioc

DEP:Differential Enrichment analysis of Proteomics data

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

Maintained by Arne Smits. Last updated 5 months ago.

immunooncology proteomics massspectrometry differentialexpression datarepresentation

7.10 score 628 scripts

bioc

alabaster.matrix:Load and Save Artifacts from File

Save matrices, arrays and similar objects into file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

Maintained by Aaron Lun. Last updated 24 days ago.

dataimport datarepresentation cpp

7.05 score 15 scripts 8 dependents

bioc

CuratedAtlasQueryR:Queries the Human Cell Atlas

Provides access to a copy of the Human Cell Atlas, but with harmonised metadata. This allows for uniform querying across numerous datasets within the Atlas using common fields such as cell type, tissue type, and patient ethnicity. Usage involves first querying the metadata table for cells of interest, and then downloading the corresponding cells into a SingleCellExperiment object.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics database duckdb hdf5 human-cell-atlas single-cell singlecellexperiment tidyverse

90 stars 7.04 score 41 scripts

bioc

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

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

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

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

15 stars 7.03 score 44 scripts

bioc

DSS:Dispersion shrinkage for sequencing data

DSS is an R library performing differntial analysis for count-based sequencing data. It detectes differentially expressed genes (DEGs) from RNA-seq, and differentially methylated loci or regions (DML/DMRs) from bisulfite sequencing (BS-seq). The core of DSS is a new dispersion shrinkage method for estimating the dispersion parameter from Gamma-Poisson or Beta-Binomial distributions.

Maintained by Hao Wu. Last updated 5 months ago.

sequencing rnaseq dnamethylation geneexpression differentialexpression differentialmethylation

7.02 score 248 scripts 5 dependents

bioc

COCOA:Coordinate Covariation Analysis

COCOA is a method for understanding epigenetic variation among samples. COCOA can be used with epigenetic data that includes genomic coordinates and an epigenetic signal, such as DNA methylation and chromatin accessibility data. To describe the method on a high level, COCOA quantifies inter-sample variation with either a supervised or unsupervised technique then uses a database of "region sets" to annotate the variation among samples. A region set is a set of genomic regions that share a biological annotation, for instance transcription factor (TF) binding regions, histone modification regions, or open chromatin regions. COCOA can identify region sets that are associated with epigenetic variation between samples and increase understanding of variation in your data.

Maintained by John Lawson. Last updated 5 months ago.

epigenetics dnamethylation atacseq dnaseseq methylseq methylationarray principalcomponent genomicvariation generegulation genomeannotation systemsbiology functionalgenomics chipseq sequencing immunooncology dna-methylation pca

10 stars 7.02 score 21 scripts

bioc

HiCExperiment:Bioconductor class for interacting with Hi-C files in R

R generic interface to Hi-C contact matrices in `.(m)cool`, `.hic` or HiC-Pro derived formats, as well as other Hi-C processed file formats. Contact matrices can be partially parsed using a random access method, allowing a memory-efficient representation of Hi-C data in R. The `HiCExperiment` class stores the Hi-C contacts parsed from local contact matrix files. `HiCExperiment` instances can be further investigated in R using the `HiContacts` analysis package.

Maintained by Jacques Serizay. Last updated 11 days ago.

hic dna3dstructure dataimport

9 stars 7.02 score 48 scripts 2 dependents

bioc

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

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

Maintained by Charlotte Soneson. Last updated 3 months ago.

statisticalmethod cellbasedassays

20 stars 7.00 score 45 scripts

bioc

h5mread:A fast HDF5 reader

The main function in the h5mread package is h5mread(), which allows reading arbitrary data from an HDF5 dataset into R, similarly to what the h5read() function from the rhdf5 package does. In the case of h5mread(), the implementation has been optimized to make it as fast and memory-efficient as possible.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure datarepresentation dataimport openssl curl zlib

1 stars 6.98 score 4 scripts 127 dependents

bioc

CoGAPS:Coordinated Gene Activity in Pattern Sets

Coordinated Gene Activity in Pattern Sets (CoGAPS) implements a Bayesian MCMC matrix factorization algorithm, GAPS, and links it to gene set statistic methods to infer biological process activity. It can be used to perform sparse matrix factorization on any data, and when this data represents biomolecules, to do gene set analysis.

Maintained by Elana J. Fertig. Last updated 18 days ago.

geneexpression transcription genesetenrichment differentialexpression bayesian clustering timecourse rnaseq microarray multiplecomparison dimensionreduction immunooncology cpp

6.97 score 104 scripts

bioc

NanoMethViz:Visualise methylation data from Oxford Nanopore sequencing

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

Maintained by Shian Su. Last updated 20 days ago.

software longread visualization differentialmethylation dnamethylation epigenetics dataimport zlib cpp

26 stars 6.95 score 11 scripts

bioc

scClassify:scClassify: single-cell Hierarchical Classification

scClassify is a multiscale classification framework for single-cell RNA-seq data based on ensemble learning and cell type hierarchies, enabling sample size estimation required for accurate cell type classification and joint classification of cells using multiple references.

Maintained by Yingxin Lin. Last updated 5 months ago.

singlecell geneexpression classification

23 stars 6.92 score 30 scripts

bioc

cliqueMS:Annotation of Isotopes, Adducts and Fragmentation Adducts for in-Source LC/MS Metabolomics Data

Annotates data from liquid chromatography coupled to mass spectrometry (LC/MS) metabolomics experiments. Based on a network algorithm (O.Senan, A. Aguilar- Mogas, M. Navarro, O. Yanes, R.Guimerà and M. Sales-Pardo, Bioinformatics, 35(20), 2019), 'CliqueMS' builds a weighted similarity network where nodes are features and edges are weighted according to the similarity of this features. Then it searches for the most plausible division of the similarity network into cliques (fully connected components). Finally it annotates metabolites within each clique, obtaining for each annotated metabolite the neutral mass and their features, corresponding to isotopes, ionization adducts and fragmentation adducts of that metabolite.

Maintained by Oriol Senan Campos. Last updated 5 months ago.

metabolomics massspectrometry network networkinference cpp

12 stars 6.91 score 25 scripts

bioc

pRolocGUI:Interactive visualisation of spatial proteomics data

The package pRolocGUI comprises functions to interactively visualise spatial proteomics data on the basis of pRoloc, pRolocdata and shiny.

Maintained by Lisa Breckels. Last updated 5 months ago.

proteomics visualization gui

8 stars 6.90 score 3 scripts

bioc

RCM:Fit row-column association models with the negative binomial distribution for the microbiome

Combine ideas of log-linear analysis of contingency table, flexible response function estimation and empirical Bayes dispersion estimation for explorative visualization of microbiome datasets. The package includes unconstrained as well as constrained analysis. In addition, diagnostic plot to detect lack of fit are available.

Maintained by Stijn Hawinkel. Last updated 5 months ago.

metagenomics dimensionreduction microbiome visualization ordination phyloseq rcm

16 stars 6.90 score 25 scripts

bioc

RnBeads:RnBeads

RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.

Maintained by Fabian Mueller. Last updated 2 months ago.

dnamethylation methylationarray methylseq epigenetics qualitycontrol preprocessing batcheffect differentialmethylation sequencing cpgisland immunooncology twochannel dataimport

6.85 score 169 scripts 1 dependents

bioc

TADCompare:TADCompare: Identification and characterization of differential TADs

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

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing featureextraction clustering

23 stars 6.74 score 10 scripts

bioc

SIAMCAT:Statistical Inference of Associations between Microbial Communities And host phenoTypes

Pipeline for Statistical Inference of Associations between Microbial Communities And host phenoTypes (SIAMCAT). A primary goal of analyzing microbiome data is to determine changes in community composition that are associated with environmental factors. In particular, linking human microbiome composition to host phenotypes such as diseases has become an area of intense research. For this, robust statistical modeling and biomarker extraction toolkits are crucially needed. SIAMCAT provides a full pipeline supporting data preprocessing, statistical association testing, statistical modeling (LASSO logistic regression) including tools for evaluation and interpretation of these models (such as cross validation, parameter selection, ROC analysis and diagnostic model plots).

Maintained by Jakob Wirbel. Last updated 5 months ago.

immunooncology metagenomics classification microbiome sequencing preprocessing clustering featureextraction geneticvariability multiplecomparison regression

6.72 score 147 scripts

bioc

CytoPipeline:Automation and visualization of flow cytometry data analysis pipelines

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

Maintained by Philippe Hauchamps. Last updated 5 months ago.

flowcytometry preprocessing qualitycontrol workflowstep immunooncology software visualization

4 stars 6.71 score 18 scripts 2 dependents

bioc

epiregulon:Gene regulatory network inference from single cell epigenomic data

Gene regulatory networks model the underlying gene regulation hierarchies that drive gene expression and observed phenotypes. Epiregulon infers TF activity in single cells by constructing a gene regulatory network (regulons). This is achieved through integration of scATAC-seq and scRNA-seq data and incorporation of public bulk TF ChIP-seq data. Links between regulatory elements and their target genes are established by computing correlations between chromatin accessibility and gene expressions.

Maintained by Xiaosai Yao. Last updated 20 days ago.

singlecell generegulation networkinference network geneexpression transcription genetarget cpp

14 stars 6.67 score 17 scripts

bioc

peakPantheR:Peak Picking and Annotation of High Resolution Experiments

An automated pipeline for the detection, integration and reporting of predefined features across a large number of mass spectrometry data files. It enables the real time annotation of multiple compounds in a single file, or the parallel annotation of multiple compounds in multiple files. A graphical user interface as well as command line functions will assist in assessing the quality of annotation and update fitting parameters until a satisfactory result is obtained.

Maintained by Arnaud Wolfer. Last updated 5 months ago.

massspectrometry metabolomics peakdetection feature-detection mass-spectrometry

12 stars 6.65 score 23 scripts

bioc

lisaClust:lisaClust: Clustering of Local Indicators of Spatial Association

lisaClust provides a series of functions to identify and visualise regions of tissue where spatial associations between cell-types is similar. This package can be used to provide a high-level summary of cell-type colocalization in multiplexed imaging data that has been segmented at a single-cell resolution.

Maintained by Ellis Patrick. Last updated 4 months ago.

singlecell cellbasedassays spatial

3 stars 6.64 score 48 scripts

bioc

CiteFuse:CiteFuse: multi-modal analysis of CITE-seq data

CiteFuse pacakage implements a suite of methods and tools for CITE-seq data from pre-processing to integrative analytics, including doublet detection, network-based modality integration, cell type clustering, differential RNA and protein expression analysis, ADT evaluation, ligand-receptor interaction analysis, and interactive web-based visualisation of the analyses.

Maintained by Yingxin Lin. Last updated 5 months ago.

singlecell geneexpression bioinformatics single-cell cpp

27 stars 6.59 score 18 scripts

bioc

LOBSTAHS:Lipid and Oxylipin Biomarker Screening through Adduct Hierarchy Sequences

LOBSTAHS is a multifunction package for screening, annotation, and putative identification of mass spectral features in large, HPLC-MS lipid datasets. In silico data for a wide range of lipids, oxidized lipids, and oxylipins can be generated from user-supplied structural criteria with a database generation function. LOBSTAHS then applies these databases to assign putative compound identities to features in any high-mass accuracy dataset that has been processed using xcms and CAMERA. Users can then apply a series of orthogonal screening criteria based on adduct ion formation patterns, chromatographic retention time, and other properties, to evaluate and assign confidence scores to this list of preliminary assignments. During the screening routine, LOBSTAHS rejects assignments that do not meet the specified criteria, identifies potential isomers and isobars, and assigns a variety of annotation codes to assist the user in evaluating the accuracy of each assignment.

Maintained by Henry Holm. Last updated 5 months ago.

immunooncology massspectrometry metabolomics lipidomics dataimport adduct algae bioconductor hplc-esi-ms lipid mass-spectrometry oxidative-stress-biomarkers oxidized-lipids oxylipins plankton

8 stars 6.56 score 9 scripts

bioc

SpectralTAD:SpectralTAD: Hierarchical TAD detection using spectral clustering

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

Maintained by Mikhail Dozmorov. Last updated 5 months ago.

software hic sequencing featureextraction clustering

8 stars 6.53 score 17 scripts

bioc

SpotClean:SpotClean adjusts for spot swapping in spatial transcriptomics data

SpotClean is a computational method to adjust for spot swapping in spatial transcriptomics data. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind mRNA. Ideally, unique molecular identifiers at a spot measure spot-specific expression, but this is often not the case due to bleed from nearby spots, an artifact we refer to as spot swapping. SpotClean is able to estimate the contamination rate in observed data and decontaminate the spot swapping effect, thus increase the sensitivity and precision of downstream analyses.

Maintained by Zijian Ni. Last updated 5 months ago.

dataimport rnaseq sequencing geneexpression spatial singlecell transcriptomics preprocessing rna-seq spatial-transcriptomics

31 stars 6.52 score 36 scripts

bioc

ChAMP:Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC

The package includes quality control metrics, a selection of normalization methods and novel methods to identify differentially methylated regions and to highlight copy number alterations.

Maintained by Yuan Tian. Last updated 5 months ago.

microarray methylationarray normalization twochannel copynumber dnamethylation

6.50 score 278 scripts

bioc

Statial:A package to identify changes in cell state relative to spatial associations

Statial is a suite of functions for identifying changes in cell state. The functionality provided by Statial provides robust quantification of cell type localisation which are invariant to changes in tissue structure. In addition to this Statial uncovers changes in marker expression associated with varying levels of localisation. These features can be used to explore how the structure and function of different cell types may be altered by the agents they are surrounded with.

Maintained by Farhan Ameen. Last updated 5 months ago.

singlecell spatial classification single-cell

5 stars 6.49 score 23 scripts

bioc

Prostar:Provides a GUI for DAPAR

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

Maintained by Samuel Wieczorek. Last updated 5 months ago.

proteomics massspectrometry normalization preprocessing software gui prostar1

1 stars 6.48 score 15 scripts

nano-optics

terms:T-matrix for Electromagnetic Radiation with Multiple Scatterers

A set of Fortran modules/routines for T-matrix-based calculations of light scattering by clusters of individual scatterers.

Maintained by Baptiste Auguié. Last updated 8 months ago.

light scattering

7 stars 6.46 score 828 scripts

bioc

MoleculeExperiment:Prioritising a molecule-level storage of Spatial Transcriptomics Data

MoleculeExperiment contains functions to create and work with objects from the new MoleculeExperiment class. We introduce this class for analysing molecule-based spatial transcriptomics data (e.g., Xenium by 10X, Cosmx SMI by Nanostring, and Merscope by Vizgen). This allows researchers to analyse spatial transcriptomics data at the molecule level, and to have standardised data formats accross vendors.

Maintained by Shila Ghazanfar. Last updated 5 months ago.

dataimport datarepresentation infrastructure software spatial transcriptomics

12 stars 6.45 score 39 scripts

adrientaudiere

MiscMetabar:Miscellaneous Functions for Metabarcoding Analysis

Facilitate the description, transformation, exploration, and reproducibility of metabarcoding analyses. 'MiscMetabar' is mainly built on top of the 'phyloseq', 'dada2' and 'targets' R packages. It helps to build reproducible and robust bioinformatics pipelines in R. 'MiscMetabar' makes ecological analysis of alpha and beta-diversity easier, more reproducible and more powerful by integrating a large number of tools. Important features are described in Taudière A. (2023) <doi:10.21105/joss.06038>.

Maintained by Adrien Taudière. Last updated 9 days ago.

sequencing microbiome metagenomics clustering classification visualization amplicon amplicon-sequencing biodiversity-informatics ecology illumina metabarcoding ngs-analysis

17 stars 6.44 score 23 scripts

bioc

SpliceWiz:interactive analysis and visualization of alternative splicing in R

The analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across conditions. SpliceWiz features a shiny-based GUI facilitating interactive data exploration of results including gene ontology enrichment. It is performance optimized with multi-threaded processing of BAM files and a new COV file format for fast recall of sequencing coverage. Overall, SpliceWiz streamlines AS analysis, enabling reliable identification of functionally relevant AS events for further characterization.

Maintained by Alex Chit Hei Wong. Last updated 17 days ago.

software transcriptomics rnaseq alternativesplicing coverage differentialsplicing differentialexpression gui sequencing cpp openmp

16 stars 6.41 score 8 scripts

bioc

quantro:A test for when to use quantile normalization

A data-driven test for the assumptions of quantile normalization using raw data such as objects that inherit eSets (e.g. ExpressionSet, MethylSet). Group level information about each sample (such as Tumor / Normal status) must also be provided because the test assesses if there are global differences in the distributions between the user-defined groups.

Maintained by Stephanie Hicks. Last updated 5 months ago.

normalization preprocessing multiplecomparison microarray sequencing

6.40 score 69 scripts 2 dependents

bioc

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

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

Maintained by Keegan Korthauer. Last updated 5 months ago.

immunooncology dnamethylation epigenetics multiplecomparison software sequencing differentialmethylation wholegenome regression functionalgenomics

6.39 score 59 scripts 1 dependents

bioc

alabaster.se:Load and Save SummarizedExperiments from File

Save SummarizedExperiments into file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

Maintained by Aaron Lun. Last updated 5 months ago.

dataimport datarepresentation

6.39 score 8 scripts 7 dependents

bioc

PrInCE:Predicting Interactomes from Co-Elution

PrInCE (Predicting Interactomes from Co-Elution) uses a naive Bayes classifier trained on dataset-derived features to recover protein-protein interactions from co-elution chromatogram profiles. This package contains the R implementation of PrInCE.

Maintained by Michael Skinnider. Last updated 5 months ago.

proteomics systemsbiology networkinference

8 stars 6.38 score 25 scripts

bioc

alabaster.ranges:Load and Save Ranges-related Artifacts from File

Save GenomicRanges, IRanges and related data structures into file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

Maintained by Aaron Lun. Last updated 5 months ago.

dataimport datarepresentation

6.38 score 8 scripts 8 dependents

bioc

scDataviz:scDataviz: single cell dataviz and downstream analyses

In the single cell World, which includes flow cytometry, mass cytometry, single-cell RNA-seq (scRNA-seq), and others, there is a need to improve data visualisation and to bring analysis capabilities to researchers even from non-technical backgrounds. scDataviz attempts to fit into this space, while also catering for advanced users. Additonally, due to the way that scDataviz is designed, which is based on SingleCellExperiment, it has a 'plug and play' feel, and immediately lends itself as flexibile and compatibile with studies that go beyond scDataviz. Finally, the graphics in scDataviz are generated via the ggplot engine, which means that users can 'add on' features to these with ease.

Maintained by Kevin Blighe. Last updated 5 months ago.

singlecell immunooncology rnaseq geneexpression transcription flowcytometry massspectrometry dataimport

63 stars 6.30 score 16 scripts

bioc

recountmethylation:Access and analyze public DNA methylation array data compilations

Resources for cross-study analyses of public DNAm array data from NCBI GEO repo, produced using Illumina's Infinium HumanMethylation450K (HM450K) and MethylationEPIC (EPIC) platforms. Provided functions enable download, summary, and filtering of large compilation files. Vignettes detail background about file formats, example analyses, and more. Note the disclaimer on package load and consult the main manuscripts for further info.

Maintained by Sean K Maden. Last updated 5 months ago.

dnamethylation epigenetics microarray methylationarray experimenthub

9 stars 6.28 score 9 scripts

bioc

signifinder:Collection and implementation of public transcriptional cancer signatures

signifinder is an R package for computing and exploring a compendium of tumor signatures. It allows to compute a variety of signatures, based on gene expression values, and return single-sample scores. Currently, signifinder contains more than 60 distinct signatures collected from the literature, relating to multiple tumors and multiple cancer processes.

Maintained by Stefania Pirrotta. Last updated 3 months ago.

geneexpression genetarget immunooncology biomedicalinformatics rnaseq microarray reportwriting visualization singlecell spatial genesignaling

7 stars 6.28 score 15 scripts

bioc

lumi:BeadArray Specific Methods for Illumina Methylation and Expression Microarrays

The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays.

Maintained by Lei Huang. Last updated 5 months ago.

microarray onechannel preprocessing dnamethylation qualitycontrol twochannel

6.26 score 294 scripts 5 dependents

bioc

flowPloidy:Analyze flow cytometer data to determine sample ploidy

Determine sample ploidy via flow cytometry histogram analysis. Reads Flow Cytometry Standard (FCS) files via the flowCore bioconductor package, and provides functions for determining the DNA ploidy of samples based on internal standards.

Maintained by Tyler Smith. Last updated 5 months ago.

flowcytometry gui regression visualization bioconductor evolution flow-cytometry polyploidy

5 stars 6.26 score 5 scripts

rickhelmus

patRoon:Workflows for Mass-Spectrometry Based Non-Target Analysis

Provides an easy-to-use interface to a mass spectrometry based non-target analysis workflow. Various (open-source) tools are combined which provide algorithms for extraction and grouping of features, extraction of MS and MS/MS data, automatic formula and compound annotation and grouping related features to components. In addition, various tools are provided for e.g. data preparation and cleanup, plotting results and automatic reporting.

Maintained by Rick Helmus. Last updated 8 days ago.

mass-spectrometry non-target cpp openjdk

65 stars 6.24 score 43 scripts

bioc

CopyNumberPlots:Create Copy-Number Plots using karyoploteR functionality

CopyNumberPlots have a set of functions extending karyoploteRs functionality to create beautiful, customizable and flexible plots of copy-number related data.

Maintained by Bernat Gel. Last updated 5 months ago.

visualization copynumbervariation coverage onechannel dataimport sequencing dnaseq bioconductor bioconductor-package bioinformatics copy-number-variation genomics genomics-visualization

6 stars 6.24 score 16 scripts 2 dependents

bioc

VariantFiltering:Filtering of coding and non-coding genetic variants

Filter genetic variants using different criteria such as inheritance model, amino acid change consequence, minor allele frequencies across human populations, splice site strength, conservation, etc.

Maintained by Robert Castelo. Last updated 2 months ago.

genetics homo_sapiens annotation snp sequencing highthroughputsequencing

4 stars 6.23 score 21 scripts

david-barnett

microViz:Microbiome Data Analysis and Visualization

Microbiome data visualization and statistics tools built upon phyloseq.

Maintained by David Barnett. Last updated 3 months ago.

microbiome microbiome-analysis microbiota

114 stars 6.22 score 480 scripts

bioc

iNETgrate:Integrates DNA methylation data with gene expression in a single gene network

The iNETgrate package provides functions to build a correlation network in which nodes are genes. DNA methylation and gene expression data are integrated to define the connections between genes. This network is used to identify modules (clusters) of genes. The biological information in each of the resulting modules is represented by an eigengene. These biological signatures can be used as features e.g., for classification of patients into risk categories. The resulting biological signatures are very robust and give a holistic view of the underlying molecular changes.

Maintained by Habil Zare. Last updated 5 months ago.

geneexpression rnaseq dnamethylation networkinference network graphandnetwork biomedicalinformatics systemsbiology transcriptomics classification clustering dimensionreduction principalcomponent mrnamicroarray normalization geneprediction kegg survival core-services

74 stars 6.21 score 1 scripts

chiliubio

file2meco:Transform Files to 'microtable' Object with 'microeco' Package

Transform output files of some tools to the 'microtable' object of 'microtable' class in 'microeco' package. The 'microtable' class is the basic class in 'microeco' package and is necessary for the downstream microbial community data analysis.

Maintained by Chi Liu. Last updated 4 months ago.

25 stars 6.12 score 75 scripts

bioc

HiContacts:Analysing cool files in R with HiContacts

HiContacts provides a collection of tools to analyse and visualize Hi-C datasets imported in R by HiCExperiment.

Maintained by Jacques Serizay. Last updated 11 days ago.

hic dna3dstructure

12 stars 6.07 score 49 scripts

bioc

metaseqR2:An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms

Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way.

Maintained by Panagiotis Moulos. Last updated 18 days ago.

software geneexpression differentialexpression workflowstep preprocessing qualitycontrol normalization reportwriting rnaseq transcription sequencing transcriptomics bayesian clustering cellbiology biomedicalinformatics functionalgenomics systemsbiology immunooncology alternativesplicing differentialsplicing multiplecomparison timecourse dataimport atacseq epigenetics regression proprietaryplatforms genesetenrichment batcheffect chipseq

7 stars 6.05 score 3 scripts

bioc

CluMSID:Clustering of MS2 Spectra for Metabolite Identification

CluMSID is a tool that aids the identification of features in untargeted LC-MS/MS analysis by the use of MS2 spectra similarity and unsupervised statistical methods. It offers functions for a complete and customisable workflow from raw data to visualisations and is interfaceable with the xmcs family of preprocessing packages.

Maintained by Tobias Depke. Last updated 5 months ago.

metabolomics preprocessing clustering

10 stars 6.04 score 22 scripts

bioc

RMassBank:Workflow to process tandem MS files and build MassBank records

Workflow to process tandem MS files and build MassBank records. Functions include automated extraction of tandem MS spectra, formula assignment to tandem MS fragments, recalibration of tandem MS spectra with assigned fragments, spectrum cleanup, automated retrieval of compound information from Internet databases, and export to MassBank records.

Maintained by RMassBank at Eawag. Last updated 5 months ago.

immunooncology bioinformatics massspectrometry metabolomics software openjdk

6.02 score 26 scripts

bioc

ENmix:Quality control and analysis tools for Illumina DNA methylation BeadChip

Tools for quanlity control, analysis and visulization of Illumina DNA methylation array data.

Maintained by Zongli Xu. Last updated 16 days ago.

dnamethylation preprocessing qualitycontrol twochannel microarray onechannel methylationarray batcheffect normalization dataimport regression principalcomponent epigenetics multichannel differentialmethylation immunooncology

6.01 score 115 scripts

bioc

EventPointer:An effective identification of alternative splicing events using junction arrays and RNA-Seq data

EventPointer is an R package to identify alternative splicing events that involve either simple (case-control experiment) or complex experimental designs such as time course experiments and studies including paired-samples. The algorithm can be used to analyze data from either junction arrays (Affymetrix Arrays) or sequencing data (RNA-Seq). The software returns a data.frame with the detected alternative splicing events: gene name, type of event (cassette, alternative 3',...,etc), genomic position, statistical significance and increment of the percent spliced in (Delta PSI) for all the events. The algorithm can generate a series of files to visualize the detected alternative splicing events in IGV. This eases the interpretation of results and the design of primers for standard PCR validation.

Maintained by Juan A. Ferrer-Bonsoms. Last updated 5 months ago.

alternativesplicing differentialsplicing mrnamicroarray rnaseq transcription sequencing timecourse immunooncology

4 stars 6.00 score 6 scripts

bioc

dar:Differential Abundance Analysis by Consensus

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

Maintained by Francesc Catala-Moll. Last updated 15 days ago.

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

2 stars 5.98 score 8 scripts

bioc

biscuiteer:Convenience Functions for Biscuit

A test harness for bsseq loading of Biscuit output, summarization of WGBS data over defined regions and in mappable samples, with or without imputation, dropping of mostly-NA rows, age estimates, etc.

Maintained by Jacob Morrison. Last updated 5 months ago.

dataimport methylseq dnamethylation

6 stars 5.98 score 16 scripts

bioc

kissDE:Retrieves Condition-Specific Variants in RNA-Seq Data

Retrieves condition-specific variants in RNA-seq data (SNVs, alternative-splicings, indels). It has been developed as a post-treatment of 'KisSplice' but can also be used with user's own data.

Maintained by Aurélie Siberchicot. Last updated 5 months ago.

alternativesplicing differentialsplicing experimentaldesign genomicvariation rnaseq transcriptomics

3 stars 5.98 score 7 scripts

bioc

consensusOV:Gene expression-based subtype classification for high-grade serous ovarian cancer

This package implements four major subtype classifiers for high-grade serous (HGS) ovarian cancer as described by Helland et al. (PLoS One, 2011), Bentink et al. (PLoS One, 2012), Verhaak et al. (J Clin Invest, 2013), and Konecny et al. (J Natl Cancer Inst, 2014). In addition, the package implements a consensus classifier, which consolidates and improves on the robustness of the proposed subtype classifiers, thereby providing reliable stratification of patients with HGS ovarian tumors of clearly defined subtype.

Maintained by Benjamin Haibe-Kains. Last updated 5 months ago.

classification clustering differentialexpression geneexpression microarray transcriptomics cancer-data cancer-genomics cancer-research expression-database ovarian-cancer

3 stars 5.98 score 15 scripts 1 dependents

bioc

simpleSeg:A package to perform simple cell segmentation

Image segmentation is the process of identifying the borders of individual objects (in this case cells) within an image. This allows for the features of cells such as marker expression and morphology to be extracted, stored and analysed. simpleSeg provides functionality for user friendly, watershed based segmentation on multiplexed cellular images in R based on the intensity of user specified protein marker channels. simpleSeg can also be used for the normalization of single cell data obtained from multiple images.

Maintained by Ellis Patrick. Last updated 5 months ago.

classification survival singlecell normalization spatial spatial-statistics

5.96 score 19 scripts 2 dependents

bioc

scFeatures:scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction

scFeatures constructs multi-view representations of single-cell and spatial data. scFeatures is a tool that generates multi-view representations of single-cell and spatial data through the construction of a total of 17 feature types. These features can then be used for a variety of analyses using other software in Biocondutor.

Maintained by Yue Cao. Last updated 5 months ago.

cellbasedassays singlecell spatial software transcriptomics

10 stars 5.95 score 15 scripts

bioc

transformGamPoi:Variance Stabilizing Transformation for Gamma-Poisson Models

Variance-stabilizing transformations help with the analysis of heteroskedastic data (i.e., data where the variance is not constant, like count data). This package provide two types of variance stabilizing transformations: (1) methods based on the delta method (e.g., 'acosh', 'log(x+1)'), (2) model residual based (Pearson and randomized quantile residuals).

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

singlecell normalization preprocessing regression cpp

21 stars 5.95 score 21 scripts

bioc

REMP:Repetitive Element Methylation Prediction

Machine learning-based tools to predict DNA methylation of locus-specific repetitive elements (RE) by learning surrounding genetic and epigenetic information. These tools provide genomewide and single-base resolution of DNA methylation prediction on RE that are difficult to measure using array-based or sequencing-based platforms, which enables epigenome-wide association study (EWAS) and differentially methylated region (DMR) analysis on RE.

Maintained by Yinan Zheng. Last updated 5 months ago.

dnamethylation microarray methylationarray sequencing genomewideassociation epigenetics preprocessing multichannel twochannel differentialmethylation qualitycontrol dataimport

2 stars 5.94 score 18 scripts

bioc

PathoStat:PathoStat Statistical Microbiome Analysis Package

The purpose of this package is to perform Statistical Microbiome Analysis on metagenomics results from sequencing data samples. In particular, it supports analyses on the PathoScope generated report files. PathoStat provides various functionalities including Relative Abundance charts, Diversity estimates and plots, tests of Differential Abundance, Time Series visualization, and Core OTU analysis.

Maintained by Solaiappan Manimaran. Last updated 5 months ago.

microbiome metagenomics graphandnetwork microarray patternlogic principalcomponent sequencing software visualization rnaseq immunooncology

8 stars 5.90 score 8 scripts

jedick

chem16S:Chemical Metrics for Microbial Communities

Combines taxonomic classifications of high-throughput 16S rRNA gene sequences with reference proteomes of archaeal and bacterial taxa to generate amino acid compositions of community reference proteomes. Calculates chemical metrics including carbon oxidation state ('Zc'), stoichiometric oxidation and hydration state ('nO2' and 'nH2O'), H/C, N/C, O/C, and S/C ratios, grand average of hydropathicity ('GRAVY'), isoelectric point ('pI'), protein length, and average molecular weight of amino acid residues. Uses precomputed reference proteomes for archaea and bacteria derived from the Genome Taxonomy Database ('GTDB'). Also includes reference proteomes derived from the NCBI Reference Sequence ('RefSeq') database and manual mapping from the 'RDP Classifier' training set to 'RefSeq' taxonomy as described by Dick and Tan (2023) <doi:10.1007/s00248-022-01988-9>. Processes taxonomic classifications in 'RDP Classifier' format or OTU tables in 'phyloseq-class' objects from the Bioconductor package 'phyloseq'.

Maintained by Jeffrey Dick. Last updated 9 days ago.

16s-rrna carbon-oxidation-state chemical-metrics genomic-adaptation microbial-communities

4 stars 5.89 score 8 scripts

bioc

MuData:Serialization for MultiAssayExperiment Objects

Save MultiAssayExperiments to h5mu files supported by muon and mudata. Muon is a Python framework for multimodal omics data analysis. It uses an HDF5-based format for data storage.

Maintained by Ilia Kats. Last updated 1 months ago.

dataimport anndata bioconductor mudata multi-omics multimodal-omics scrna-seq

5 stars 5.89 score 26 scripts

bioc

HiCDOC:A/B compartment detection and differential analysis

HiCDOC normalizes intrachromosomal Hi-C matrices, uses unsupervised learning to predict A/B compartments from multiple replicates, and detects significant compartment changes between experiment conditions. It provides a collection of functions assembled into a pipeline to filter and normalize the data, predict the compartments and visualize the results. It accepts several type of data: tabular `.tsv` files, Cooler `.cool` or `.mcool` files, Juicer `.hic` files or HiC-Pro `.matrix` and `.bed` files.

Maintained by Maigné Élise. Last updated 4 months ago.

hic dna3dstructure normalization sequencing software clustering cpp

4 stars 5.86 score 6 scripts 1 dependents

vdblab

FLORAL:Fit Log-Ratio Lasso Regression for Compositional Data

Log-ratio Lasso regression for continuous, binary, and survival outcomes with (longitudinal) compositional features. See Fei and others (2024) <doi:10.1016/j.crmeth.2024.100899>.

Maintained by Teng Fei. Last updated 1 months ago.

openblas cpp openmp

12 stars 5.85 score 13 scripts

bioc

escape:Easy single cell analysis platform for enrichment

A bridging R package to facilitate gene set enrichment analysis (GSEA) in the context of single-cell RNA sequencing. Using raw count information, Seurat objects, or SingleCellExperiment format, users can perform and visualize ssGSEA, GSVA, AUCell, and UCell-based enrichment calculations across individual cells.

Maintained by Nick Borcherding. Last updated 8 days ago.

software singlecell classification annotation genesetenrichment sequencing genesignaling pathways

5.84 score 138 scripts

guokai8

microbial:Do 16s Data Analysis and Generate Figures

Provides functions to enhance the available statistical analysis procedures in R by providing simple functions to analysis and visualize the 16S rRNA data.Here we present a tutorial with minimum working examples to demonstrate usage and dependencies.

Maintained by Kai Guo. Last updated 6 months ago.

software graphandnetwork microbiome microbiome-analysis

13 stars 5.81 score 25 scripts

bioc

SpatialExperimentIO:Read in Xenium, CosMx, MERSCOPE or STARmapPLUS data as SpatialExperiment object

Read in imaging-based spatial transcriptomics technology data. Current available modules are for Xenium by 10X Genomics, CosMx by Nanostring, MERSCOPE by Vizgen, or STARmapPLUS from Broad Institute. You can choose to read the data in as a SpatialExperiment or a SingleCellExperiment object.

Maintained by Yixing E. Dong. Last updated 2 months ago.

datarepresentation dataimport infrastructure transcriptomics singlecell spatial geneexpression

9 stars 5.81 score 16 scripts

bioc

EGSEA:Ensemble of Gene Set Enrichment Analyses

This package implements the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing. EGSEA algorithm utilizes the analysis results of twelve prominent GSE algorithms in the literature to calculate collective significance scores for each gene set.

Maintained by Monther Alhamdoosh. Last updated 5 months ago.

immunooncology differentialexpression go geneexpression genesetenrichment genetics microarray multiplecomparison onechannel pathways rnaseq sequencing software systemsbiology twochannel metabolomics proteomics kegg graphandnetwork genesignaling genetarget networkenrichment network classification

5.81 score 64 scripts

bioc

RPA:RPA: Robust Probabilistic Averaging for probe-level analysis

Probabilistic analysis of probe reliability and differential gene expression on short oligonucleotide arrays.

Maintained by Leo Lahti. Last updated 5 months ago.

geneexpression microarray preprocessing qualitycontrol

5.78 score 20 scripts 1 dependents

bioc

deconvR:Simulation and Deconvolution of Omic Profiles

This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of the reference cell types.The package includes the cell-type-specific methylation atlas and, Illumina Epic B5 probe ids that can be used in deconvolution. Additionally,we included BSmeth2Probe, to make mapping WGBS data to their probe IDs easier.

Maintained by Irem B. Gündüz. Last updated 5 months ago.

dnamethylation regression geneexpression rnaseq singlecell statisticalmethod transcriptomics bioconductor-package deconvolution dna-methylation omics

10 stars 5.78 score 15 scripts

bioc

benchdamic:Benchmark of differential abundance methods on microbiome data

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

Maintained by Matteo Calgaro. Last updated 4 months ago.

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

8 stars 5.78 score 8 scripts

bioc

TENxIO:Import methods for 10X Genomics files

Provides a structured S4 approach to importing data files from the 10X pipelines. It mainly supports Single Cell Multiome ATAC + Gene Expression data among other data types. The main Bioconductor data representations used are SingleCellExperiment and RaggedExperiment.

Maintained by Marcel Ramos. Last updated 4 months ago.

software infrastructure dataimport singlecell bioconductor-package u24ca289073

5.77 score 7 scripts 3 dependents

bioc

scRNAseqApp:A single-cell RNAseq Shiny app-package

The scRNAseqApp is a Shiny app package designed for interactive visualization of single-cell data. It is an enhanced version derived from the ShinyCell, repackaged to accommodate multiple datasets. The app enables users to visualize data containing various types of information simultaneously, facilitating comprehensive analysis. Additionally, it includes a user management system to regulate database accessibility for different users.

Maintained by Jianhong Ou. Last updated 16 days ago.

visualization singlecell rnaseq interactive-visualizations multiple-users shiny-apps single-cell-rna-seq

4 stars 5.76 score 3 scripts

adafede

cascade:Contextualizing untargeted Annotation with Semi-quantitative Charged Aerosol Detection for pertinent characterization of natural Extracts

This package provides the infrastructure to perform Automated Composition Assessment of Natural Extracts.

Maintained by Adriano Rutz. Last updated 2 days ago.

metabolite annotation charged aerosol detector semi-quantitative natural products computational metabolomics specialized metabolome

2 stars 5.76 score 40 scripts 1 dependents

bioc

flowAI:Automatic and interactive quality control for flow cytometry data

The package is able to perform an automatic or interactive quality control on FCS data acquired using flow cytometry instruments. By evaluating three different properties: 1) flow rate, 2) signal acquisition, 3) dynamic range, the quality control enables the detection and removal of anomalies.

Maintained by Gianni Monaco. Last updated 5 months ago.

flowcytometry qualitycontrol biomedicalinformatics immunooncology

5.67 score 86 scripts 3 dependents

bioc

cydar:Using Mass Cytometry for Differential Abundance Analyses

Identifies differentially abundant populations between samples and groups in mass cytometry data. Provides methods for counting cells into hyperspheres, controlling the spatial false discovery rate, and visualizing changes in abundance in the high-dimensional marker space.

Maintained by Aaron Lun. Last updated 5 months ago.

immunooncology flowcytometry multiplecomparison proteomics singlecell cpp

5.64 score 48 scripts

bioc

flowMeans:Non-parametric Flow Cytometry Data Gating

Identifies cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection. Note: R 2.11.0 or newer is required.

Maintained by Nima Aghaeepour. Last updated 5 months ago.

immunooncology flowcytometry cellbiology clustering

5.64 score 36 scripts 2 dependents

bioc

diffHic:Differential Analysis of Hi-C Data

Detects differential interactions across biological conditions in a Hi-C experiment. Methods are provided for read alignment and data pre-processing into interaction counts. Statistical analysis is based on edgeR and supports normalization and filtering. Several visualization options are also available.

Maintained by Aaron Lun. Last updated 3 months ago.

multiplecomparison preprocessing sequencing coverage alignment normalization clustering hic curl bzip2 xz-utils zlib cpp

5.58 score 38 scripts

bioc

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

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

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

bayesian classification clustering immunooncology qualitycontrol dataimport proteomics massspectrometry openblas cpp openmp

4 stars 5.56 score 3 scripts

bioc

multicrispr:Multi-locus multi-purpose Crispr/Cas design

This package is for designing Crispr/Cas9 and Prime Editing experiments. It contains functions to (1) define and transform genomic targets, (2) find spacers (4) count offtarget (mis)matches, and (5) compute Doench2016/2014 targeting efficiency. Care has been taken for multicrispr to scale well towards large target sets, enabling the design of large Crispr/Cas9 libraries.

Maintained by Aditya Bhagwat. Last updated 4 months ago.

crispr software

5.56 score 2 scripts

bioc

BgeeCall:Automatic RNA-Seq present/absent gene expression calls generation

BgeeCall allows to generate present/absent gene expression calls without using an arbitrary cutoff like TPM<1. Calls are generated based on reference intergenic sequences. These sequences are generated based on expression of all RNA-Seq libraries of each species integrated in Bgee (https://bgee.org).

Maintained by Julien Wollbrett. Last updated 5 months ago.

software geneexpression rnaseq biology gene-expression gene-level intergenic-regions present-absent-calls rna-seq rna-seq-libraries scrna-seq

3 stars 5.56 score 9 scripts

bioc

scifer:Scifer: Single-Cell Immunoglobulin Filtering of Sanger Sequences

Have you ever index sorted cells in a 96 or 384-well plate and then sequenced using Sanger sequencing? If so, you probably had some struggles to either check the electropherogram of each cell sequenced manually, or when you tried to identify which cell was sorted where after sequencing the plate. Scifer was developed to solve this issue by performing basic quality control of Sanger sequences and merging flow cytometry data from probed single-cell sorted B cells with sequencing data. scifer can export summary tables, 'fasta' files, electropherograms for visual inspection, and generate reports.

Maintained by Rodrigo Arcoverde Cerveira. Last updated 4 months ago.

preprocessing qualitycontrol sangerseq sequencing software flowcytometry singlecell

5 stars 5.54 score 9 scripts

bioc

methylclock:Methylclock - DNA methylation-based clocks

This package allows to estimate chronological and gestational DNA methylation (DNAm) age as well as biological age using different methylation clocks. Chronological DNAm age (in years) : Horvath's clock, Hannum's clock, BNN, Horvath's skin+blood clock, PedBE clock and Wu's clock. Gestational DNAm age : Knight's clock, Bohlin's clock, Mayne's clock and Lee's clocks. Biological DNAm clocks : Levine's clock and Telomere Length's clock.

Maintained by Dolors Pelegri-Siso. Last updated 5 months ago.

dnamethylation biologicalquestion preprocessing statisticalmethod normalization cpp

39 stars 5.52 score 28 scripts

bioc

VisiumIO:Import Visium data from the 10X Space Ranger pipeline

The package allows users to readily import spatial data obtained from either the 10X website or from the Space Ranger pipeline. Supported formats include tar.gz, h5, and mtx files. Multiple files can be imported at once with *List type of functions. The package represents data mainly as SpatialExperiment objects.

Maintained by Marcel Ramos. Last updated 2 months ago.

software infrastructure dataimport singlecell spatial bioconductor-package genomics u24ca289073

5.50 score 14 scripts 1 dependents

bioc

cytoviewer:An interactive multi-channel image viewer for R

This R package supports interactive visualization of multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques using shiny. The cytoviewer interface is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with SingleCellExperiment and SpatialExperiment objects for metadata visualization and supports image downloads.

Maintained by Lasse Meyer. Last updated 5 months ago.

immunooncology software singlecell onechannel twochannel multichannel spatial dataimport bioconductor imaging shiny visualization

7 stars 5.50 score 15 scripts

krisrs1128

multimedia:Multimodal Mediation Analysis

Multimodal mediation analysis is an emerging problem in microbiome data analysis. Multimedia make advanced mediation analysis techniques easy to use, ensuring that all statistical components are transparent and adaptable to specific problem contexts. The package provides a uniform interface to direct and indirect effect estimation, synthetic null hypothesis testing, bootstrap confidence interval construction, and sensitivity analysis. More details are available in Jiang et al. (2024) "multimedia: Multimodal Mediation Analysis of Microbiome Data" <doi:10.1101/2024.03.27.587024>.

Maintained by Kris Sankaran. Last updated 1 months ago.

coverage microbiome regression sequencing software statisticalmethod structuralequationmodels causal-inference data-integration mediation-analysis

1 stars 5.49 score 13 scripts

bioc

conumee:Enhanced copy-number variation analysis using Illumina DNA methylation arrays

This package contains a set of processing and plotting methods for performing copy-number variation (CNV) analysis using Illumina 450k or EPIC methylation arrays.

Maintained by Volker Hovestadt. Last updated 5 months ago.

copynumbervariation dnamethylation methylationarray microarray normalization preprocessing qualitycontrol software

5.48 score 30 scripts

bioc

bigmelon:Illumina methylation array analysis for large experiments

Methods for working with Illumina arrays using gdsfmt.

Maintained by Leonard C. Schalkwyk. Last updated 5 months ago.

dnamethylation microarray twochannel preprocessing qualitycontrol methylationarray dataimport cpgisland

5.47 score 21 scripts

bioc

SurfR:Surface Protein Prediction and Identification

Identify Surface Protein coding genes from a list of candidates. Systematically download data from GEO and TCGA or use your own data. Perform DGE on bulk RNAseq data. Perform Meta-analysis. Descriptive enrichment analysis and plots.

Maintained by Aurora Maurizio. Last updated 15 days ago.

software sequencing rnaseq geneexpression transcription differentialexpression principalcomponent genesetenrichment pathways batcheffect functionalgenomics visualization dataimport functionalprediction geneprediction go dge enrichment-analysis metaanalysis plots proteins public-data surface surfaceome

3 stars 5.43 score 3 scripts

bioc

alabaster.sce:Load and Save SingleCellExperiment from File

Save SingleCellExperiment into file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

Maintained by Aaron Lun. Last updated 5 months ago.

dataimport datarepresentation

5.43 score 4 scripts 3 dependents

bioc

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

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

Maintained by Samuel Wieczorek. Last updated 5 months ago.

proteomics normalization preprocessing massspectrometry qualitycontrol go dataimport prostar1

2 stars 5.42 score 22 scripts 1 dependents

bioc

RITAN:Rapid Integration of Term Annotation and Network resources

Tools for comprehensive gene set enrichment and extraction of multi-resource high confidence subnetworks. RITAN facilitates bioinformatic tasks for enabling network biology research.

Maintained by Michael Zimmermann. Last updated 5 months ago.

qualitycontrol network networkenrichment networkinference genesetenrichment functionalgenomics graphandnetwork

5.40 score 9 scripts

igordot

clustermole:Unbiased Single-Cell Transcriptomic Data Cell Type Identification

Assignment of cell type labels to single-cell RNA sequencing (scRNA-seq) clusters is often a time-consuming process that involves manual inspection of the cluster marker genes complemented with a detailed literature search. This is especially challenging when unexpected or poorly described populations are present. The clustermole R package provides methods to query thousands of human and mouse cell identity markers sourced from a variety of databases.

Maintained by Igor Dolgalev. Last updated 1 years ago.

cell-type cell-type-annotation cell-type-classification cell-type-identification cell-type-matching gene-expression-signatures scrna-seq single-cell

13 stars 5.37 score 36 scripts

bioc

visiumStitched:Enable downstream analysis of Visium capture areas stitched together with Fiji

This package provides helper functions for working with multiple Visium capture areas that overlap each other. This package was developed along with the companion example use case data available from https://github.com/LieberInstitute/visiumStitched_brain. visiumStitched prepares SpaceRanger (10x Genomics) output files so you can stitch the images from groups of capture areas together with Fiji. Then visiumStitched builds a SpatialExperiment object with the stitched data and makes an artificial hexogonal grid enabling the seamless use of spatial clustering methods that rely on such grid to identify neighboring spots, such as PRECAST and BayesSpace. The SpatialExperiment objects created by visiumStitched are compatible with spatialLIBD, which can be used to build interactive websites for stitched SpatialExperiment objects. visiumStitched also enables casting SpatialExperiment objects as Seurat objects.

Maintained by Nicholas J. Eagles. Last updated 4 months ago.

software spatial transcriptomics transcription geneexpression visualization dataimport 10xgenomics bioconductor spatial-transcriptomics spatialexperiment spatiallibd visium

1 stars 5.36 score 4 scripts

jfukuyama

adaptiveGPCA:Adaptive Generalized PCA

Implements adaptive gPCA, as described in: Fukuyama, J. (2017) <arXiv:1702.00501>. The package also includes functionality for applying the method to 'phyloseq' objects so that the method can be easily applied to microbiome data and a 'shiny' app for interactive visualization.

Maintained by Julia Fukuyama. Last updated 2 years ago.

9 stars 5.33 score 24 scripts

bioc

omXplore:Vizualization tools for 'omics' datasets with R

This package contains a collection of functions (written as shiny modules) for the visualisation and the statistical analysis of omics data. These plots can be displayed individually or embedded in a global Shiny module. Additionaly, it is possible to integrate third party modules to the main interface of the package omXplore.

Maintained by Samuel Wieczorek. Last updated 2 days ago.

software shinyapps massspectrometry datarepresentation gui qualitycontrol prostar2

5.32 score 23 scripts

bioc

scCB2:CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data

scCB2 is an R package implementing CB2 for distinguishing real cells from empty droplets in droplet-based single cell RNA-seq experiments (especially for 10x Chromium). It is based on clustering similar barcodes and calculating Monte-Carlo p-value for each cluster to test against background distribution. This cluster-level test outperforms single-barcode-level tests in dealing with low count barcodes and homogeneous sequencing library, while keeping FDR well controlled.

Maintained by Zijian Ni. Last updated 5 months ago.

dataimport rnaseq singlecell sequencing geneexpression transcriptomics preprocessing clustering

10 stars 5.30 score 5 scripts

bioc

DegCre:Probabilistic association of DEGs to CREs from differential data

DegCre generates associations between differentially expressed genes (DEGs) and cis-regulatory elements (CREs) based on non-parametric concordance between differential data. The user provides GRanges of DEG TSS and CRE regions with differential p-value and optionally log-fold changes and DegCre returns an annotated Hits object with associations and their calculated probabilities. Additionally, the package provides functionality for visualization and conversion to other formats.

Maintained by Brian S. Roberts. Last updated 4 months ago.

geneexpression generegulation atacseq chipseq dnaseseq rnaseq

5 stars 5.30 score 2 scripts

bioc

DeMixT:Cell type-specific deconvolution of heterogeneous tumor samples with two or three components using expression data from RNAseq or microarray platforms

DeMixT is a software package that performs deconvolution on transcriptome data from a mixture of two or three components.

Maintained by Ruonan Li. Last updated 5 months ago.

software statisticalmethod classification geneexpression sequencing microarray tissuemicroarray coverage cpp openmp

5.27 score 25 scripts

bioc

CytoMDS:Low Dimensions projection of cytometry samples

This package implements a low dimensional visualization of a set of cytometry samples, in order to visually assess the 'distances' between them. This, in turn, can greatly help the user to identify quality issues like batch effects or outlier samples, and/or check the presence of potential sample clusters that might align with the exeprimental design. The CytoMDS algorithm combines, on the one hand, the concept of Earth Mover's Distance (EMD), a.k.a. Wasserstein metric and, on the other hand, the Multi Dimensional Scaling (MDS) algorithm for the low dimensional projection. Also, the package provides some diagnostic tools for both checking the quality of the MDS projection, as well as tools to help with the interpretation of the axes of the projection.

Maintained by Philippe Hauchamps. Last updated 2 months ago.

flowcytometry qualitycontrol dimensionreduction multidimensionalscaling software visualization

1 stars 5.23 score 2 scripts

bioc

methylCC:Estimate the cell composition of whole blood in DNA methylation samples

A tool to estimate the cell composition of DNA methylation whole blood sample measured on any platform technology (microarray and sequencing).

Maintained by Stephanie C. Hicks. Last updated 5 months ago.

microarray sequencing dnamethylation methylationarray methylseq wholegenome

19 stars 5.18 score 8 scripts

bioc

CNVfilteR:Identifies false positives of CNV calling tools by using SNV calls

CNVfilteR identifies those CNVs that can be discarded by using the single nucleotide variant (SNV) calls that are usually obtained in common NGS pipelines.

Maintained by Jose Marcos Moreno-Cabrera. Last updated 5 months ago.

copynumbervariation sequencing dnaseq visualization dataimport

5 stars 5.18 score 1 scripts

bioc

flowDensity:Sequential Flow Cytometry Data Gating

This package provides tools for automated sequential gating analogous to the manual gating strategy based on the density of the data.

Maintained by Mehrnoush Malek. Last updated 5 months ago.

bioinformatics flowcytometry cellbiology clustering cancer flowcytdata datarepresentation stemcell densitygating

5.17 score 83 scripts 3 dependents

bioc

ptairMS:Pre-processing PTR-TOF-MS Data

This package implements a suite of methods to preprocess data from PTR-TOF-MS instruments (HDF5 format) and generates the 'sample by features' table of peak intensities in addition to the sample and feature metadata (as a singl<e ExpressionSet object for subsequent statistical analysis). This package also permit usefull tools for cohorts management as analyzing data progressively, visualization tools and quality control. The steps include calibration, expiration detection, peak detection and quantification, feature alignment, missing value imputation and feature annotation. Applications to exhaled air and cell culture in headspace are described in the vignettes and examples. This package was used for data analysis of Gassin Delyle study on adults undergoing invasive mechanical ventilation in the intensive care unit due to severe COVID-19 or non-COVID-19 acute respiratory distress syndrome (ARDS), and permit to identfy four potentiel biomarquers of the infection.

Maintained by camille Roquencourt. Last updated 5 months ago.

software massspectrometry preprocessing metabolomics peakdetection alignment cpp

7 stars 5.15 score 3 scripts

timothy-barry

ondisc:Algorithms and data structures for large single-cell expression matrices

Single-cell datasets are growing in size, posing challenges as well as opportunities for genomics researchers. `ondisc` is an R package that facilitates analysis of large-scale single-cell data out-of-core on a laptop or distributed across tens to hundreds processors on a cluster or cloud. In both of these settings, `ondisc` requires only a few gigabytes of memory, even if the input data are tens of gigabytes in size. `ondisc` mainly is oriented toward single-cell CRISPR screen analysis, but ondisc also can be used for single-cell differential expression and single-cell co-expression analyses. ondisc is powered by several new, efficient algorithms for manipulating and querying large, sparse expression matrices.

Maintained by Timothy Barry. Last updated 12 months ago.

dataimport singlecell differentialexpression crispr zlib cpp

11 stars 5.13 score 62 scripts

bioc

squallms:Speedy quality assurance via lasso labeling for LC-MS data

squallms is a Bioconductor R package that implements a "semi-labeled" approach to untargeted mass spectrometry data. It pulls in raw data from mass-spec files to calculate several metrics that are then used to label MS features in bulk as high or low quality. These metrics of peak quality are then passed to a simple logistic model that produces a fully-labeled dataset suitable for downstream analysis.

Maintained by William Kumler. Last updated 5 months ago.

massspectrometry metabolomics proteomics lipidomics shinyapps classification clustering featureextraction principalcomponent regression preprocessing qualitycontrol visualization

3 stars 5.13 score 5 scripts

bioc

geomeTriD:A R/Bioconductor package for interactive 3D plot of epigenetic data or single cell data

geomeTriD (Three Dimensional Geometry Package) create interactive 3D plots using the GL library with the 'three.js' visualization library (https://threejs.org) or the rgl library. In addition to creating interactive 3D plots, the application also generates simplified models in 2D. These 2D models provide a more straightforward visual representation, making it easier to analyze and interpret the data quickly. This functionality ensures that users have access to both detailed three-dimensional visualizations and more accessible two-dimensional views, catering to various analytical needs.

Maintained by Jianhong Ou. Last updated 2 months ago.

visualization

1 stars 5.10 score 7 scripts

bioc

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

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

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

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

5 stars 5.08 score 16 scripts

bioc

topdownr:Investigation of Fragmentation Conditions in Top-Down Proteomics

The topdownr package allows automatic and systemic investigation of fragment conditions. It creates Thermo Orbitrap Fusion Lumos method files to test hundreds of fragmentation conditions. Additionally it provides functions to analyse and process the generated MS data and determine the best conditions to maximise overall fragment coverage.

Maintained by Sebastian Gibb. Last updated 5 months ago.

immunooncology infrastructure proteomics massspectrometry coverage mass-spectrometry topdown

1 stars 5.08 score

bioc

chevreulShiny:Tools for managing SingleCellExperiment objects as projects

Tools for managing SingleCellExperiment objects as projects. Includes functions for analysis and visualization of single-cell data. Also included is a shiny app for visualization of pre-processed scRNA data. Supported by NIH grants R01CA137124 and R01EY026661 to David Cobrinik.

Maintained by Kevin Stachelek. Last updated 26 days ago.

coverage rnaseq sequencing visualization geneexpression transcription singlecell transcriptomics normalization preprocessing qualitycontrol dimensionreduction dataimport

5.08 score

bioc

yamss:Tools for high-throughput metabolomics

Tools to analyze and visualize high-throughput metabolomics data aquired using chromatography-mass spectrometry. These tools preprocess data in a way that enables reliable and powerful differential analysis. At the core of these methods is a peak detection phase that pools information across all samples simultaneously. This is in contrast to other methods that detect peaks in a sample-by-sample basis.

Maintained by Leslie Myint. Last updated 5 months ago.

massspectrometry metabolomics peakdetection software

3 stars 5.08 score 9 scripts

lanl

NEONiso:Tools to Calibrate and Work with NEON Atmospheric Isotope Data

Functions for downloading, calibrating, and analyzing atmospheric isotope data bundled into the eddy covariance data products of the National Ecological Observatory Network (NEON) <https://www.neonscience.org>. Calibration tools are provided for carbon and water isotope products. Carbon isotope calibration details are found in Fiorella et al. (2021) <doi:10.1029/2020JG005862>, and the readme file at <https://github.com/lanl/NEONiso>. Tools for calibrating water isotope products have been added as of 0.6.0, but have known deficiencies and should be considered experimental and unsupported.

Maintained by Rich Fiorella. Last updated 1 months ago.

2 stars 5.08 score 6 scripts

bioc

MSnID:Utilities for Exploration and Assessment of Confidence of LC-MSn Proteomics Identifications

Extracts MS/MS ID data from mzIdentML (leveraging mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximum number of identifications while not exceeding a specified false discovery rate. Also contains a number of utilities to explore the MS/MS results and assess missed and irregular enzymatic cleavages, mass measurement accuracy, etc.

Maintained by Vlad Petyuk. Last updated 5 months ago.

proteomics massspectrometry immunooncology

5.06 score 57 scripts

bioc

alabaster.spatial:Save and Load Spatial 'Omics Data to/from File

Save SpatialExperiment objects and their images into file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

Maintained by Aaron Lun. Last updated 5 months ago.

dataimport datarepresentation

5.02 score 5 scripts 1 dependents

bioc

shinyepico:ShinyÉPICo

ShinyÉPICo is a graphical pipeline to analyze Illumina DNA methylation arrays (450k or EPIC). It allows to calculate differentially methylated positions and differentially methylated regions in a user-friendly interface. Moreover, it includes several options to export the results and obtain files to perform downstream analysis.

Maintained by Octavio Morante-Palacios. Last updated 5 months ago.

differentialmethylation dnamethylation microarray preprocessing qualitycontrol

5 stars 5.00 score 1 scripts

bioc

GSCA:GSCA: Gene Set Context Analysis

GSCA takes as input several lists of activated and repressed genes. GSCA then searches through a compendium of publicly available gene expression profiles for biological contexts that are enriched with a specified pattern of gene expression. GSCA provides both traditional R functions and interactive, user-friendly user interface.

Maintained by Zhicheng Ji. Last updated 5 months ago.

geneexpression visualization gui

5.00 score 5 scripts

lcrawlab

smer:Sparse Marginal Epistasis Test

The Sparse Marginal Epistasis Test is a computationally efficient genetics method which detects statistical epistasis in complex traits; see Stamp et al. (2025, <doi:10.1101/2025.01.11.632557>) for details.

Maintained by Julian Stamp. Last updated 2 months ago.

genomewideassociation epistasis genetics snp linearmixedmodel cpp epistasis-analysis epistatis gwas gwas-tools mapit zlib cpp openmp

1 stars 4.95 score 8 scripts

bioc

alabaster.string:Save and Load Biostrings to/from File

Save Biostrings objects to file artifacts, and load them back into memory. This is a more portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

Maintained by Aaron Lun. Last updated 5 months ago.

dataimport datarepresentation

4.95 score 5 scripts 2 dependents

bioc

epigraHMM:Epigenomic R-based analysis with hidden Markov models

epigraHMM provides a set of tools for the analysis of epigenomic data based on hidden Markov Models. It contains two separate peak callers, one for consensus peaks from biological or technical replicates, and one for differential peaks from multi-replicate multi-condition experiments. In differential peak calling, epigraHMM provides window-specific posterior probabilities associated with every possible combinatorial pattern of read enrichment across conditions.

Maintained by Pedro Baldoni. Last updated 5 months ago.

chipseq atacseq dnaseseq hiddenmarkovmodel epigenetics zlib openblas cpp openmp

4.94 score 88 scripts

bioc

scMitoMut:Single-cell Mitochondrial Mutation Analysis Tool

This package is designed for calling lineage-informative mitochondrial mutations using single-cell sequencing data, such as scRNASeq and scATACSeq (preferably the latter due to RNA editing issues). It includes functions for mutation calling and visualization. Mutation calling is done using beta-binomial distribution.

Maintained by Wenjie Sun. Last updated 3 months ago.

preprocessing sequencing singlecell openblas cpp

2 stars 4.90 score 5 scripts