| Literature DB >> 32728687 |
Zhixu Qiu1, Siyuan Chen1, Yuhong Qi1, Chunni Liu1, Jingjing Zhai1, Shang Xie1, Chuang Ma2.
Abstract
Transcriptional switch (TS) is a widely observed phenomenon caused by changes in the relative expression of transcripts from the same gene, in spatial, temporal or other dimensions. TS has been associated with human diseases, plant development and stress responses. Its investigation is often hampered by a lack of suitable tools allowing comprehensive and flexible TS analysis for high-throughput RNA sequencing (RNA-Seq) data. Here, we present deepTS, a user-friendly web-based implementation that enables a fully interactive, multifunctional identification, visualization and analysis of TS events for large-scale RNA-Seq datasets from pairwise, temporal and population experiments. deepTS offers rich functionality to streamline RNA-Seq-based TS analysis for both model and non-model organisms and for those with or without reference transcriptome. The presented case studies highlight the capabilities of deepTS and demonstrate its potential for the transcriptome-wide TS analysis of pairwise, temporal and population RNA-Seq data. We believe deepTS will help research groups, regardless of their informatics expertise, perform accessible, reproducible and collaborative TS analyses of large-scale RNA-Seq data.Entities:
Keywords: Galaxy; RNA-Seq; pipeline; transcriptional switch; workflow
Year: 2021 PMID: 32728687 DOI: 10.1093/bib/bbaa137
Source DB: PubMed Journal: Brief Bioinform ISSN: 1467-5463 Impact factor: 11.622