44
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      dbHT-Trans: An Efficient Tool for Filtering the Protein-Encoding Transcripts Assembled by RNA-Seq According to Search for Homologous Proteins.

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In RNA-Seq studies, there are still many challenges for reliably assembling transcripts. Both genome-guided and de novo methods always produce too many false transcripts because of known and unknown factors. Therefore, the postassembly quality filtering is necessary before performing downstream analyses. Here, we present an automatic and efficient tool of dbHT-Trans for filtering the protein-encoding transcripts assembled by RNA-Seq. For each candidate transcript, we first deduced all potential open reading frames and translated them into amino acid sequences. By searching against the reference protein database, a transcript would be predicted a false one when it has no homologous sequence. Using this method, it is expected to filter out the falsely assembled transcripts of protein-encoding genes. Application of dbHT-Trans to the annotated transcriptome of mouse revealed that the sensitivity was almost 90% for recalling protein-encoding transcripts. After this quality filtering, the numbers of assembled genes became more consistent between Cufflinks and Trinity tools. To significantly decrease the data storage, we transformed all intermediate data into descriptive metadata and stored by the MySQL database, which will be utilized by downstream analyses in a real-time style. The source codes, example data, and manual of dbHT-Trans are freely available on the GitHub repository.

          Related collections

          Author and article information

          Journal
          J. Comput. Biol.
          Journal of computational biology : a journal of computational molecular cell biology
          1557-8666
          1066-5277
          Jan 2016
          : 23
          : 1
          Affiliations
          [1 ] Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University , Chengdu, China .
          Article
          10.1089/cmb.2015.0137
          26484655
          ca0effdb-508f-47f0-9c59-ff675e768a11
          History

          RNA-Seq,quality filtering,transcript
          RNA-Seq, quality filtering, transcript

          Comments

          Comment on this article