Iterative error correction of long sequencing reads maximizes accuracy and improves contig assembly

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Katrin Sameith - , Max Planck Institute of Molecular Cell Biology and Genetics (Author)
  • Juliana G Roscito - , Max Planck Institute of Molecular Cell Biology and Genetics (Author)
  • Michael Hiller - (Author)

Abstract

Next-generation sequencers such as Illumina can now produce reads up to 300 bp with high throughput, which is attractive for genome assembly. A first step in genome assembly is to computationally correct sequencing errors. However, correcting all errors in these longer reads is challenging. Here, we show that reads with remaining errors after correction often overlap repeats, where short erroneous k-mers occur in other copies of the repeat. We developed an iterative error correction pipeline that runs the previously published String Graph Assembler (SGA) in multiple rounds of k-mer-based correction with an increasing k-mer size, followed by a final round of overlap-based correction. By combining the advantages of small and large k-mers, this approach corrects more errors in repeats and minimizes the total amount of erroneous reads. We show that higher read accuracy increases contig lengths two to three times. We provide SGA-Iteratively Correcting Errors (https://github.com/hillerlab/IterativeErrorCorrection/) that implements iterative error correction by using modules from SGA.

Details

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalBriefings in bioinformatics
Volume18
Issue number1
Publication statusPublished - Jan 2017
Peer-reviewedYes
Externally publishedYes

External IDs

PubMedCentral PMC5221426
Scopus 85015830340
ORCID /0000-0003-4306-930X/work/141545247
ORCID /0000-0003-1494-1162/work/142255068

Keywords

Keywords

  • Algorithms, High-Throughput Nucleotide Sequencing, Sequence Analysis, DNA