deepTS is a powerful and flexible web-based Galaxy platform for identifying, visualizing and analyzing transcriptional switch (TS) events from pairwise, temporal and population transcriptome data. deepTS consists of three main functional modules, covering the processes of read cleaning and mapping, transcriptome map construction, expression abundance estimation, multiple-condition TS analysis pipelines, multiple-level TS characterization, and multiple-form visualization to allow users to perform TS analysis using either raw RNA-Seq data or expression abundance matrix directly.
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- Please cite the following article:
Qiu Z., Chen, S., Qi Y., Liu C., Zhai J., Xie S., Ma, C. (2020). Exploring transcriptional switches from pairwise, temporal, and population RNA-Seq data using deepTS Briefings in Bioinformatics https://dx.doi.org/10.1093/bib/bbaa137
Chuang Ma
Professor, Doctoral Supervisor
My research interests include artificial intelligence, abiotic stress and plant breeding.