DUDE-Seq: Fast, flexible, and robust denoising for targeted amplicon sequencing.

ABSTRACT: We consider the correction of errors from nucleotide sequences produced by next-generation targeted amplicon sequencing. The next-generation sequencing (NGS) platforms can provide a great deal of sequencing data thanks to their high throughput, but the associated error rates often tend to be high. Denoising in high-throughput sequencing has thus become a crucial process for boosting the reliability of downstream analyses. Our methodology, named DUDE-Seq, is derived from a general setting of reconstructing finite-valued source data corrupted by a discrete memoryless channel and effectively corrects substitution and homopolymer indel errors, the two major types of sequencing errors in most high-throughput targeted amplicon sequencing platforms. Our experimental studies with real and simulate

SUBMITTER: Lee B 

PROVIDER: S-EPMC5531809 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature