{ "_id": "6a186e1bacfb0bcc41dc2c78", "Package": "epiregulon", "Title": "Gene regulatory network inference from single cell epigenomic\ndata", "Version": "2.2.0", "Date": "2025-12-08", "Authors@R": "c(person(given = \"Xiaosai\", family = \"Yao\", role = c(\"aut\", \"cre\"), email = \"xiaosai.yao@gmail.com\", comment = c(ORCID = \"0000-0001-9729-0726\")),\nperson(given = \"Tomasz\", family = \"Włodarczyk\", role = c(\"aut\"), email = \"tomwlo@gmail.com\", comment = c(ORCID = \"0000-0003-1554-9699\")),\nperson(given = \"Aaron\", family = \"Lun\", role=c(\"aut\"), email=\"infinite.monkeys.with.keyboards@gmail.com\"),\nperson(given = \"Shang-Yang\", family = \"Chen\", role = \"aut\", email = \"sychen9584@gmail.com\"))", "Description": "Gene regulatory networks model the underlying gene\nregulation hierarchies that drive gene expression and observed\nphenotypes. Epiregulon infers TF activity in single cells by\nconstructing a gene regulatory network (regulons). This is\nachieved through integration of scATAC-seq and scRNA-seq data\nand incorporation of public bulk TF ChIP-seq data. Links\nbetween regulatory elements and their target genes are\nestablished by computing correlations between chromatin\naccessibility and gene expressions.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "URL": "https://github.com/xiaosaiyao/epiregulon/", "biocViews": "SingleCell, GeneRegulation,NetworkInference,Network,\nGeneExpression, Transcription, GeneTarget", "Config/testthat/edition": "3", "BugReports": "https://github.com/xiaosaiyao/epiregulon/issues", "Config/pak/sysreqs": "libglpk-dev make libgsl0-dev libbz2-dev libicu-dev\nliblzma-dev libpng-dev libxml2-dev libssl-dev xz-utils\nzlib1g-dev", "Repository": "https://bioc-release.r-universe.dev", "Date/Publication": "2026-04-28 13:03:07 UTC", "RemoteUrl": "https://github.com/bioc/epiregulon", "RemoteRef": "RELEASE_3_23", "RemoteSha": "90785b2698e28a599b6def878a67dbb325bcdc82", "NeedsCompilation": "yes", "Packaged": { "Date": 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