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.
Last updated 28 days ago
singlecellgeneregulationnetworkinferencenetworkgeneexpressiontranscriptiongenetarget
12 stars 6.61 score 205 dependenciesepiregulon.extra - Companion package to epiregulon with additional plotting, differential and graph functions
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.
Last updated 7 days ago
generegulationnetworkgeneexpressiontranscriptionchiponchipdifferentialexpressiongenetargetnormalizationgraphandnetwork
5.11 score 175 dependencies