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deepTS is a powerful and flexible web-based Galaxy platform for identifying, visualizing and analyzing transcriptional switch events from pairwise, temporal and population transcriptome data.
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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 matrices directly.
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deepTS project is hosted on GitHub (https://github.com/cma2015/deepTS). A demo server is available at (http://www.omicstudio.cloud:4009/). We suggest users to run deepTS locally using the Docker image (https://hub.docker.com/r/malab/deepts).
- Module I: Generation of transcript expression matrix
- Module II: Identification of TS events
- Module III: Exploration of TS events
- Docker image of deepTS were released for the first time.
- Source codes, web server of deepTS were released for the first time.
- For any bugs/issues, please feel free to leave a message at Github issues. We will try our best to deal with all issues as soon as possible.
- For any suggestions/comments, please send emails to: Siyuan Chen [email protected] or Zhixu Qiu [email protected]
Zhixu Qiu, Siyuan Chen, Yuhong Qi, Chunni Liu, Jingjing Zhai, Shang Xie, Chuang Ma, Exploring transcriptional switch events from pairwise, temporal, and population transcriptome data using deepTS. Briefings in Bioinformatics, 2020, doi:10.1093/bib/bbaa137