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

Yukiteru Ono, Kiyoshi Asai, Michiaki Hamada*


研究成果: Article査読

39 被引用数 (Scopus)


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. We evaluated our developed simulator from various points, indicating that our simulator successfully simulates reads that are consistent with real reads. Availability and implementation: The source codes of PBSIM2 are freely available from https://github.com/yukiter uono/pbsim2.

出版ステータスPublished - 2021 3月 1

ASJC Scopus subject areas

  • 統計学および確率
  • 生化学
  • 分子生物学
  • コンピュータ サイエンスの応用
  • 計算理論と計算数学
  • 計算数学


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