Package: epiregulon 1.1.2

Xiaosai Yao

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.

Authors:Xiaosai Yao [aut, cre], Tomasz Włodarczyk [aut], Aaron Lun [aut], Shang-Yang Chen [aut]

epiregulon_1.1.2.tar.gz
epiregulon_1.1.2.zip(r-4.5)epiregulon_1.1.2.zip(r-4.4)epiregulon_1.1.2.zip(r-4.3)
epiregulon_1.1.2.tgz(r-4.4-arm64)epiregulon_1.1.2.tgz(r-4.4-x86_64)epiregulon_1.1.2.tgz(r-4.3-arm64)epiregulon_1.1.2.tgz(r-4.3-x86_64)
epiregulon_1.1.2.tar.gz(r-4.5-noble)epiregulon_1.1.2.tar.gz(r-4.4-noble)
epiregulon_1.1.2.tgz(r-4.4-emscripten)epiregulon_1.1.0.tgz(r-4.3-emscripten)
epiregulon.pdf |epiregulon.html✨
epiregulon/json (API)
NEWS

# Install 'epiregulon' in R:

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

Bug tracker:https://github.com/xiaosaiyao/epiregulon/issues

Uses libs:

c++– GNU Standard C++ Library v3

On BioConductor:epiregulon-1.1.0(bioc 3.20)epiregulon-1.0.1(bioc 3.19)

bioconductor-package

11 exports 2.05 score 200 dependencies

Last updated 24 days agofrom:7a809fbc00

Exports:addLogFC addMotifScore addTFMotifInfo addWeights aggregateAcrossCells aggregateAcrossCellsFast calculateActivity calculateP2G getRegulon getTFMotifInfo pruneRegulon

Dependencies:abind annotate AnnotationDbi AnnotationHub askpass AUCell AzureAuth AzureGraph AzureRMR AzureStor backports base64enc beachmat BH Biobase BiocBaseUtils BiocFileCache BiocGenerics BiocIO BiocManager BiocNeighbors BiocParallel BiocSingular BiocVersion Biostrings bit bit64 bitops blob bluster BSgenome BSgenome.Hsapiens.UCSC.hg19 BSgenome.Hsapiens.UCSC.hg38 BSgenome.Mmusculus.UCSC.mm10 bslib cachem caTools checkmate cli clipr cluster CNEr codetools colorspace cpp11 crayon crosstalk curl data.table DBI dbplyr DelayedArray DelayedMatrixStats digest DirichletMultinomial dplyr dqrng edgeR entropy evaluate ExperimentHub fansi farver fastmap filelock fontawesome formatR fs futile.logger futile.options generics GenomeInfoDb GenomeInfoDbData GenomicAlignments GenomicRanges ggplot2 glue GO.db graph GSEABase gtable gtools HDF5Array highr hms htmltools htmlwidgets httr igraph IRanges irlba isoband jose jquerylib jsonlite KEGGREST kernlab knitr labeling lambda.r later lattice lazyeval lifecycle limma locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise metapod mgcv mime mixtools motifmatchr MultiAssayExperiment munsell nlme openssl pillar pkgconfig plogr plotly plyr png poweRlaw pracma prettyunits progress promises purrr pwalign R.methodsS3 R.oo R.utils R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppHNSW RCurl readr reshape2 restfulr rhdf5 rhdf5filters Rhdf5lib Rhtslib rjson rlang rmarkdown Rsamtools RSQLite rsvd rtracklayer S4Arrays S4Vectors sass ScaledMatrix scales scMultiome scran scuttle segmented seqLogo SingleCellExperiment sitmo snow SparseArray sparseMatrixStats statmod stringi stringr SummarizedExperiment survival sys TFBSTools TFMPvalue tibble tidyr tidyselect tinytex tzdb UCSC.utils utf8 uuid vctrs viridisLite vroom withr xfun XML xml2 xtable XVector yaml zlibbioc

Epiregulon tutorial with MultiAssayExperiment

Xiaosai Yao

Rendered frommultiome.mae.Rmdusingknitr::rmarkdownon Jun 17 2024.

Last update: 2024-06-16
Started: 2022-09-12

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Add log fold changes of gene expression to regulons	addLogFC
Add Motif Scores	addMotifScore
Add TF binding motif occupancy information to the peak2gene object	addTFMotifInfo
Calculate weights for the regulons by computing co-association between TF and target gene expression	addWeights
Aggregate expression across cells	aggregateAcrossCells
Aggregate cells in SingleCellExperiment	aggregateAcrossCellsFast
Calculate the per cell activity of master regulators based on a regulon	calculateActivity
Establish peak to gene links based on correlations between ATAC-seq peaks and RNA-seq genes	calculateP2G
Combine the TF binding info and peak to gene correlations to generate regulons	getRegulon
Retrieve TF binding sites or motif positions	getTFMotifInfo
Prune regulons for true transcription factor - regulatory elements - target genes relationships	pruneRegulon