Empirical estimation of sequencing error rates using smoothing splines.

ABSTRACT:

Background

Next-generation sequencing has been used by investigators to address a diverse range of biological problems through, for example, polymorphism and mutation discovery and microRNA profiling. However, compared to conventional sequencing, the error rates for next-generation sequencing are often higher, which impacts the downstream genomic analysis. Recently, Wang et al. (BMC Bioinformatics 13:185, 2012) proposed a shadow regression approach to estimate the error rates for next-generation sequencing data based on the assumption of a linear relationship between the number of reads sequenced and the number of reads containing errors (denoted as shadows). However, this linear read-shadow relationship may not be appropriate for all types of sequence data. Therefore, it is necess

SUBMITTER: Zhu X 

PROVIDER: S-EPMC4840868 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature