ArticleBMC bioinformatics2018
NGmerge: merging paired-end reads via novel empirically-derived models of sequencing errors.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 149 papers.
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149 citing papers in PubMed.
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89 more citing papers are in PubMed but not listed here.
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1 author.
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Abstract
backgroundAdvances 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.
resultsWe 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.
conclusionsWe 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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