Flexible analysis of TSS mapping data and detection of TSS shifts with TSRexploreR

Abstract

Heterogeneity in transcription initiation has important consequences for transcript stability and translation, and shifts in transcription start site (TSS) usage are prevalent in various developmental, metabolic, and disease contexts. Accordingly, numerous methods for global TSS profiling have been developed, including most recently Survey of TRanscription Initiation at Promoter Elements with high-throughput sequencing (STRIPE-seq), a method to profile transcription start sites (TSSs) on a genome-wide scale with significant cost and time savings compared to previous methods. In anticipation of more widespread adoption of STRIPE-seq and related methods for construction of promoter atlases and studies of differential gene expression, we built TSRexploreR, an R package for end-to-end analysis of TSS mapping data. TSRexploreR provides functions for TSS and transcription start region (TSR) detection, normalization, correlation, visualization, and differential TSS/TSR analyses. TSRexploreR is highly interoperable, accepting the data structures of TSS and TSR sets generated by several existing tools for processing and alignment of TSS mapping data, such as CAGEr for Cap Analysis of Gene Expression (CAGE) data. Lastly, TSRexploreR implements a novel approach for the detection of shifts in TSS distribution.