TSSr: an R package for comprehensive analyses of TSS sequencing data

Author:

Lu Zhaolian1,Berry Keenan2,Hu Zhenbin1,Zhan Yu1,Ahn Tae-Hyuk23,Lin Zhenguo12ORCID

Affiliation:

1. Department of Biology, Saint Louis University, St. Louis, MO 63103, USA

2. Program of Bioinformatics and Computational Biology, Saint Louis University, St. Louis, MO 63103, USA

3. Department of Computer Sciences, Saint Louis University, St. Louis, MO 63103, USA

Abstract

Abstract Transcription initiation is regulated in a highly organized fashion to ensure proper cellular functions. Accurate identification of transcription start sites (TSSs) and quantitative characterization of transcription initiation activities are fundamental steps for studies of regulated transcriptions and core promoter structures. Several high-throughput techniques have been developed to sequence the very 5′end of RNA transcripts (TSS sequencing) on the genome scale. Bioinformatics tools are essential for processing, analysis, and visualization of TSS sequencing data. Here, we present TSSr, an R package that provides rich functions for mapping TSS and characterizations of structures and activities of core promoters based on all types of TSS sequencing data. Specifically, TSSr implements several newly developed algorithms for accurately identifying TSSs from mapped sequencing reads and inference of core promoters, which are a prerequisite for subsequent functional analyses of TSS data. Furthermore, TSSr also enables users to export various types of TSS data that can be visualized by genome browser for inspection of promoter activities in association with other genomic features, and to generate publication-ready TSS graphs. These user-friendly features could greatly facilitate studies of transcription initiation based on TSS sequencing data. The source code and detailed documentations of TSSr can be freely accessed at https://github.com/Linlab-slu/TSSr.

Funder

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

General Medicine

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