DOI: 10.18129/B9.bioc.ChromSCape    

This is the development version of ChromSCape; for the stable release version, see ChromSCape.

Analysis of single-cell epigenomics datasets with a Shiny App

Bioconductor version: Development (3.13)

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

Author: Pacome Prompsy <pacome.prompsy at>, Celine Vallot <celine.vallot at>

Maintainer: Pacome Prompsy <pacome.prompsy at>

Citation (from within R, enter citation("ChromSCape")):


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biocViews ATACSeq, Annotation, BatchEffect, ChIPSeq, Classification, Clustering, DifferentialPeakCalling, Epigenetics, GeneSetEnrichment, MethylSeq, MultipleComparison, Normalization, Pathways, Preprocessing, PrincipalComponent, QualityControl, ReportWriting, SingleCell, Software, Visualization
Version 1.1.1
In Bioconductor since BioC 3.12 (R-4.0) (< 6 months)
License GPL-3
Depends R (>= 4.0)
Imports shiny, colourpicker, shinyjs, rtracklayer, shinyFiles, shinyhelper, shinycssloaders, Matrix, plotly, shinydashboard, colorRamps, kableExtra, viridis, batchelor, BiocParallel, parallel, Rsamtools, ggplot2, qualV, stringdist, fs, qs, DT, scran, scater, ConsensusClusterPlus, Rtsne, dplyr, tidyr, GenomicRanges, IRanges, irlba, rlist, umap, tibble, methods, jsonlite, edgeR, stats, graphics, grDevices, utils, S4Vectors, SingleCellExperiment, SummarizedExperiment, msigdbr, qs, Sushi, forcats
Suggests testthat, knitr, rmarkdown, BiocStyle
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