groHMM

groHMM is an innovative computational tool developed to harness the wealth of Global run-on sequencing (GRO-seq) data. This technique illuminates the landscape of coding and non-coding RNA transcripts, including primary miRNAs, lncRNAs, eRNAs, and other yet-to-be-discovered transcript types. The software operates on R and employs a two-state hidden Markov model (HMM) to, de novo, identify the boundaries of transcription units, providing a novel approach to transcriptome analysis that surpasses existing methodologies like SICER and HOMER in identifying broad transcriptional regions.

Through systematic application to GRO-seq data from various cell types, including non-transformed and transformed human cells, as well as non-mammalian species, groHMM has demonstrated its versatility and effectiveness. Notably, its utility extends beyond mere transcription unit annotation, enabling the investigation of cell type-specific enhancers by analyzing newly annotated enhancer transcripts.