Iterative error correction of long sequencing reads maximizes accuracy and improves contig assembly
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
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 language | English |
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Pages (from-to) | 1-8 |
Number of pages | 8 |
Journal | Briefings in bioinformatics |
Volume | 18 |
Issue number | 1 |
Publication status | Published - Jan 2017 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
PubMedCentral | PMC5221426 |
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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