PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores.

ABSTRACT:

Motivation

Recent advances in high-throughput long-read sequencers, such as PacBio and Oxford Nanopore sequencers, produce longer reads with more errors than short-read sequencers. In addition to the high error rates of reads, non-uniformity of errors leads to difficulties in various downstream analyses using long reads. Many useful simulators, which characterize long-read error patterns and simulate them, have been developed. However, there is still room for improvement in the simulation of the non-uniformity of errors.

Results

To capture characteristics of errors in reads for long-read sequencers, here, we introduce a generative model for quality scores, in which a hidden Markov Model with a latest model selection method, called factorized information criteria, is utilized

SUBMITTER: Ono Y 

PROVIDER: S-EPMC8097687 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature