proovread: large-scale high-accuracy PacBio correction through iterative short read consensus

Bioinformatics. 2014 Nov 1;30(21):3004-11. doi: 10.1093/bioinformatics/btu392. Epub 2014 Jul 10.

Abstract

Motivation: Today, the base code of DNA is mostly determined through sequencing by synthesis as provided by the Illumina sequencers. Although highly accurate, resulting reads are short, making their analyses challenging. Recently, a new technology, single molecule real-time (SMRT) sequencing, was developed that could address these challenges, as it generates reads of several thousand bases. But, their broad application has been hampered by a high error rate. Therefore, hybrid approaches that use high-quality short reads to correct erroneous SMRT long reads have been developed. Still, current implementations have great demands on hardware, work only in well-defined computing infrastructures and reject a substantial amount of reads. This limits their usability considerably, especially in the case of large sequencing projects.

Results: Here we present proovread, a hybrid correction pipeline for SMRT reads, which can be flexibly adapted on existing hardware and infrastructure from a laptop to a high-performance computing cluster. On genomic and transcriptomic test cases covering Escherichia coli, Arabidopsis thaliana and human, proovread achieved accuracies up to 99.9% and outperformed the existing hybrid correction programs. Furthermore, proovread-corrected sequences were longer and the throughput was higher. Thus, proovread combines the most accurate correction results with an excellent adaptability to the available hardware. It will therefore increase the applicability and value of SMRT sequencing.

Availability and implementation: proovread is available at the following URL: http://proovread.bioapps.biozentrum.uni-wuerzburg.de.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Arabidopsis / genetics
  • Base Sequence
  • Consensus Sequence*
  • Escherichia coli / genetics
  • Gene Expression Profiling
  • Genomics
  • Humans
  • Sequence Analysis, DNA / methods*
  • Software