rnaQUAST: a quality assessment tool for de novo transcriptome assemblies

Elena Bushmanova; Dmitry Antipov; Alla Lapidus; Vladimir Suvorov; Andrey D Prjibelski

doi:10.1093/bioinformatics/btw218

rnaQUAST: a quality assessment tool for de novo transcriptome assemblies

Bioinformatics. 2016 Jul 15;32(14):2210-2. doi: 10.1093/bioinformatics/btw218. Epub 2016 Apr 23.

Authors

Elena Bushmanova¹, Dmitry Antipov¹, Alla Lapidus², Vladimir Suvorov³, Andrey D Prjibelski²

Affiliations

¹ Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
² Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia.
³ Research and Development Department, EMC, St. Petersburg, Russia.

PMID: 27153654
DOI: 10.1093/bioinformatics/btw218

Abstract

Ability to generate large RNA-Seq datasets created a demand for both de novo and reference-based transcriptome assemblers. However, while many transcriptome assemblers are now available, there is still no unified quality assessment tool for RNA-Seq assemblies. We present rnaQUAST-a tool for evaluating RNA-Seq assembly quality and benchmarking transcriptome assemblers using reference genome and gene database. rnaQUAST calculates various metrics that demonstrate completeness and correctness levels of the assembled transcripts, and outputs them in a user-friendly report.

Availability and implementation: rnaQUAST is implemented in Python and is freely available at http://bioinf.spbau.ru/en/rnaquast

Contact: ap@bioinf.spbau.ru

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Computational Biology / methods*
Sequence Analysis, RNA*
Software*
Transcriptome*