Source: r-bioc-grohmm Maintainer: Debian R Packages Maintainers Uploaders: Steffen Moeller Section: gnu-r Testsuite: autopkgtest-pkg-r Priority: optional Build-Depends: debhelper-compat (= 13), dh-r, r-base-dev, r-cran-mass, r-bioc-s4vectors, r-bioc-iranges, r-bioc-genomeinfodb, r-bioc-genomicranges, r-bioc-genomicalignments, r-bioc-rtracklayer Standards-Version: 4.6.1 Vcs-Browser: https://salsa.debian.org/r-pkg-team/r-bioc-grohmm Vcs-Git: https://salsa.debian.org/r-pkg-team/r-bioc-grohmm.git Homepage: https://bioconductor.org/packages/groHMM/ Rules-Requires-Root: no Package: r-bioc-grohmm Architecture: any Depends: ${R:Depends}, ${shlibs:Depends}, ${misc:Depends} Recommends: ${R:Recommends} Suggests: ${R:Suggests} Description: GRO-seq Analysis Pipeline This BioConductor package provides a pipeline for the analysis of GRO- seq data. Among the more advanced features, r-bioc-grohmm predicts the boundaries of transcriptional activity across the genome de novo using a two-state hidden Markov model (HMM). . The used model essentially divides the genome into transcribed and non- transcribed regions in a strand specific manner. HMMs are used to identify the leading edge of Pol II at genes activated by a stimulus in GRO-seq time course data. This approach allows the genome-wide interrogation of transcription rates in cells.