Package: ATACCoGAPS 1.7.0

Rossin Erbe

ATACCoGAPS: Analysis Tools for scATACseq Data with CoGAPS

Provides tools for running the CoGAPS algorithm (Fertig et al, 2010) on single-cell ATAC sequencing data and analysis of the results. Can be used to perform analyses at the level of genes, motifs, TFs, or pathways. Additionally provides tools for transfer learning and data integration with single-cell RNA sequencing data.

Authors:Rossin Erbe [aut, cre]

ATACCoGAPS_1.7.0.tar.gz
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ATACCoGAPS.pdf |ATACCoGAPS.html✨
ATACCoGAPS/json (API)
NEWS

# Install 'ATACCoGAPS' in R:

install.packages('ATACCoGAPS', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fertiglab/ataccogaps/issues

Datasets:

exampleMotifList - Example list of motifs for examples
schepCellTypes - Cell types corresponding to subsetSchepData
schepCogapsResult - CogapsResult from the subsetSchepData object
schepGranges - GRanges corresponding to subsetSchepData
schepPeaks - Peaks corresponding to subsetSchepData
subsetSchepData - Small subset of the scATAC-seq data from Schep et al, 2017, Nature Methods paper.
tfData - List of human TFs and motifs from cisBP database

On BioConductor:ATACCoGAPS-1.7.0(bioc 3.20)ATACCoGAPS-1.6.0(bioc 3.19)

bioconductor-package

20 exports 0.36 score 247 dependencies

Last updated 2 months agofrom:1dfb9599b2

Exports:applyGREAT ATACTransferLearning cgapsPlot dataSubsetBySparsity findRegulatoryNetworks foldAccessibility geneAccessibility genePatternMatch getTFDescriptions getTFs heatmapGeneAccessibility heatmapPatternMarkers heatmapPatternMatrix motifPatternMatch motifSummarization pathwayMatch patternMarkerCellClassifier peaksToGRanges RNAseqTFValidation simpleMotifTFMatch

Dependencies:abind annotate AnnotationDbi askpass babelgene backports base64enc BH Biobase BiocFileCache BiocGenerics BiocIO BiocManager BiocParallel biomaRt Biostrings bit bit64 bitops blob broom BSgenome BSgenome.Hsapiens.UCSC.hg19 BSgenome.Mmusculus.UCSC.mm10 bslib cachem callr caTools cellranger chromVAR circlize cli clipr cluster CNEr codetools CoGAPS colorspace commonmark conflicted cowplot cpp11 crayon crosstalk curl data.table DBI dbplyr DelayedArray digest DirichletMultinomial doParallel dplyr DT dtplyr evaluate fansi farver fastmap fastmatch fgsea filelock fontawesome forcats foreach formatR fs futile.logger futile.options gargle GeneOverlap generics GenomeInfoDb GenomeInfoDbData GenomicAlignments GenomicFeatures GenomicRanges GetoptLong ggalluvial ggplot2 ggrepel GlobalOptions glue GO.db googledrive googlesheets4 gplots graph gridBase gridExtra gtable gtools haven here highr hms Homo.sapiens htmltools htmlwidgets httpuv httr httr2 ids IRanges isoband iterators JASPAR2016 jquerylib jsonlite KEGGREST KernSmooth knitr labeling lambda.r later lattice lazyeval lifecycle limma lubridate magrittr MASS Matrix MatrixGenerics MatrixModels matrixStats memoise mgcv mime miniUI modelr motifmatchr msigdbr munsell Mus.musculus nabor nlme NMF openssl org.Hs.eg.db org.Mm.eg.db OrganismDbi pillar pkgconfig plogr plotly plyr png poweRlaw pracma prettyunits processx progress projectR promises ps purrr pwalign R.methodsS3 R.oo R.utils R6 ragg rappdirs RBGL RColorBrewer Rcpp RcppArmadillo RcppEigen RcppTOML RCurl readr readxl registry rematch rematch2 reprex reshape2 restfulr reticulate rGREAT rhdf5 rhdf5filters Rhdf5lib Rhtslib rjson rlang rmarkdown rngtools ROCR rprojroot Rsamtools RSpectra RSQLite rstudioapi rtracklayer Rtsne rvest S4Arrays S4Vectors sass scales selectr seqLogo shape shiny SingleCellExperiment snow sourcetools SparseArray statmod stringi stringr SummarizedExperiment sys systemfonts textshaping TFBSTools TFMPvalue tibble tidyr tidyselect tidyverse timechange tinytex tsne TxDb.Hsapiens.UCSC.hg19.knownGene TxDb.Hsapiens.UCSC.hg38.knownGene TxDb.Mmusculus.UCSC.mm10.knownGene txdbmaker tzdb UCSC.utils umap utf8 uuid vctrs viridis viridisLite vroom withr xfun XML xml2 xtable XVector yaml zlibbioc

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Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Find Enrichment of GO Terms in PatternMarker Peaks using GREAT	applyGREAT
Transfer Learning between ATACseq data sets using projectR	ATACTransferLearning
Plot Individual CoGAPS Patterns	cgapsPlot
Filter scATACseq by sparsity	dataSubsetBySparsity
Example list of motifs for examples	exampleMotifList
Estimate fold Accessibility of a Gene Relative to Average	foldAccessibility
Find the accessibility of the peaks overlapping a set of genes and their promoters	geneAccessibility
Match genes to pattern differentiating peaks	genePatternMatch
Heatmap Gene Accessibility	heatmapGeneAccessibility
Create Heatmap of PatternMarker Peaks	heatmapPatternMarkers
Plot the patternMatrix as a heatmap	heatmapPatternMatrix
Find Motifs and TFs from PatternMarker Peaks	findRegulatoryNetworks getTFDescriptions getTFs motifPatternMatch
Map Peaks to DNA motifs in scATAC-seq Data	motifSummarization
Matches list of genes to pathways	pathwayMatch
Match cells to patterns	patternMarkerCellClassifier
List of peaks to GRanges	peaksToGRanges
Validate TF Findings with RNA-seq CoGAPS	RNAseqTFValidation
Cell types corresponding to subsetSchepData	schepCellTypes
CogapsResult from the subsetSchepData object	schepCogapsResult
GRanges corresponding to subsetSchepData	schepGranges
Peaks corresponding to subsetSchepData	schepPeaks
Motif/TF Matching in a Single Function	simpleMotifTFMatch
Small subset of the scATAC-seq data from Schep et al, 2017, Nature Methods paper.	subsetSchepData
List of human TFs and motifs from cisBP database	tfData