TransRate: reference-free quality assessment of de novo transcriptome assemblies

  1. Steven Kelly3
  1. 1Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom;
  2. 2Department of Computer Science, Stony Brook University, Stony Brook, New York 11794-4400, USA;
  3. 3Department of Plant Sciences, University of Oxford, Oxford OX1 3RB, United Kingdom
  1. Corresponding author: steven.kelly{at}plants.ox.ac.uk

Abstract

TransRate is a tool for reference-free quality assessment of de novo transcriptome assemblies. Using only the sequenced reads and the assembly as input, we show that multiple common artifacts of de novo transcriptome assembly can be readily detected. These include chimeras, structural errors, incomplete assembly, and base errors. TransRate evaluates these errors to produce a diagnostic quality score for each contig, and these contig scores are integrated to evaluate whole assemblies. Thus, TransRate can be used for de novo assembly filtering and optimization as well as comparison of assemblies generated using different methods from the same input reads. Applying the method to a data set of 155 published de novo transcriptome assemblies, we deconstruct the contribution that assembly method, read length, read quantity, and read quality make to the accuracy of de novo transcriptome assemblies and reveal that variance in the quality of the input data explains 43% of the variance in the quality of published de novo transcriptome assemblies. Because TransRate is reference-free, it is suitable for assessment of assemblies of all types of RNA, including assemblies of long noncoding RNA, rRNA, mRNA, and mixed RNA samples.

Footnotes

  • [Supplemental material is available for this article.]

  • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.196469.115.

  • Freely available online through the Genome Research Open Access option.

  • Received July 2, 2015.
  • Accepted May 27, 2016.

This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.

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