NGmerge: merging paired-end reads via novel empirically-derived models of sequencing errors

Background Advances in Illumina DNA sequencing technology have produced longer paired-end reads that increasingly have sequence overlaps. These reads can be merged into a single read that spans the full length of the original DNA fragment, allowing for error correction and accurate determination of...

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Veröffentlicht in:BMC bioinformatics Jg. 19; H. 1; S. 536 - 9
1. Verfasser: Gaspar, John M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 20.12.2018
BioMed Central Ltd
Springer Nature B.V
BMC
Schlagworte:
Algorithms
Analysis
Bioinformatics
Biomedical and Life Sciences
Cancer
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Deoxyribonucleic acid
DNA
DNA sequencing
Empirical analysis
Error correction
Error correction & detection
Genomes
High-Throughput Nucleotide Sequencing - methods
High-throughput sequencing
Humans
Illumina paired-end sequencing
Life Sciences
Methodology
Methodology Article
Microarrays
Nucleotide sequence
Open source software
Quality
Read merging
Sequence analysis (methods)
Sequence Analysis, DNA - methods
sequencing errors; quality scores; PhiX
Source programs
High-throughput sequencing
Illumina paired-end sequencing
Read merging
sequencing errors; quality scores; PhiX
ISSN:1471-2105, 1471-2105
Online-Zugang:Volltext
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Zusammenfassung:Background Advances in Illumina DNA sequencing technology have produced longer paired-end reads that increasingly have sequence overlaps. These reads can be merged into a single read that spans the full length of the original DNA fragment, allowing for error correction and accurate determination of read coverage. Extant merging programs utilize simplistic or unverified models for the selection of bases and quality scores for the overlapping region of merged reads. Results We first examined the baseline quality score - error rate relationship using sequence reads derived from PhiX. In contrast to numerous published reports, we found that the quality scores produced by Illumina were not substantially inflated above the theoretical values, once the reference genome was corrected for unreported sequence variants. The PhiX reads were then used to create empirical models of sequencing errors in overlapping regions of paired-end reads, and these models were incorporated into a novel merging program, NGmerge. We demonstrate that NGmerge corrects errors and ambiguous bases better than other merging programs, and that it assigns quality scores for merged bases that accurately reflect the error rates. Our results also show that, contrary to published analyses, the sequencing errors of paired-end reads are not independent. Conclusions We provide a free and open-source program, NGmerge, that performs better than existing read merging programs. NGmerge is available on GitHub ( https://github.com/harvardinformatics/NGmerge ) under the MIT License; it is written in C and supported on Linux.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-018-2579-2