Training alignment parameters for arbitrary sequencers with LAST-TRAIN.

Hamada, Michiaki; Ono, Yukiteru; Asai, Kiyoshi; Frith, Martin C · Bioinformatics · 2017

basic_science · Level V

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Abstract

LAST-TRAIN improves sequence alignment accuracy by inferring substitution and gap scores that fit the frequencies of substitutions, insertions, and deletions in a given dataset. We have applied it to mapping DNA reads from IonTorrent and PacBio RS, and we show that it reduces reference bias for Oxford Nanopore reads. the source code is freely available at http://last.cbrc.jp/. mhamada@waseda.jp or mcfrith@edu.k.u-tokyo.ac.jp. Supplementary data are available at Bioinformatics online.

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