r-bioc-grohmm - 1.40.3-2 main

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.