Abstract
BackgroundThe high error rate of next generation sequencing (NGS) restricts some of its applications, such as monitoring virus mutations and detecting rare mutations in tumors. There are two commonly employed sequencing library preparation strategies to improve sequencing accuracy by correcting sequencing errors: read-pairing method and tag-clustering method (i.e. primer ID or UID). Here, we constructed a homogeneous library from a single clone, and compared the variant calling accuracy of these error-correction methods.ResultWe comprehensively described the strengths and pitfalls of these methods. We found that both read-pairing and tag-clustering methods significantly decreased sequencing error rate. While the read-pairing method was more effective than the tag-clustering method at correcting insertion and deletion errors, it was not as effective as the tag-clustering method at correcting substitution errors. In addition, we observed that when the read quality was poor, the tag-clustering method led to huge coverage loss. We also tested the effect of applying quality score filtering to the error-correction methods and demonstrated that quality score filtering was able to impose a minor, yet statistically significant improvement to the error-correction methods tested in this study.ConclusionOur study provides a benchmark for researchers to select suitable error-correction methods based on the goal of the experiment by balancing the trade-off between sequencing cost (i.e. sequencing coverage requirement) and detection sensitivity.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2388-9) contains supplementary material, which is available to authorized users.
Highlights
The high error rate of generation sequencing (NGS) restricts some of its applications, such as monitoring virus mutations and detecting rare mutations in tumors
Our study provides a benchmark for researchers to select suitable error-correction methods based on the goal of the experiment by balancing the trade-off between sequencing cost and detection sensitivity
To resolve the problems associated with the high error rate, experimental methods have been developed for distinguishing real mutations from sequencing errors
Summary
The high error rate of generation sequencing (NGS) restricts some of its applications, such as monitoring virus mutations and detecting rare mutations in tumors. To resolve the problems associated with the high error rate, experimental methods have been developed for distinguishing real mutations from sequencing errors. One such method is to take advantage of the paired-end feature of Illumina sequencing by removing the inconsistent forward and reverse read pairs [1,2,3,4,5]. Another common approach is to use nucleotide tags [6,7,8,9,10,11,12]. The same tag would be observed in different reads
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