Accel-Align: a fast sequence mapper and aligner based on the seed-embed-extend method.

ABSTRACT:

Background

Improvements in sequencing technology continue to drive sequencing cost towards $100 per genome. However, mapping sequenced data to a reference genome remains a computationally-intensive task due to the dependence on edit distance for dealing with INDELs and mismatches introduced by sequencing. All modern aligners use seed-filter-extend methodology and rely on filtration heuristics to reduce the overhead of edit distance computation. However, filtering has inherent performance-accuracy trade-offs that limits its effectiveness.

Results

Motivated by algorithmic advances in randomized low-distortion embedding, we introduce SEE, a new methodology for developing sequence mappers and aligners. While SFE focuses on eliminating sub-optimal candidates, SEE focuses instead

SUBMITTER: Yan Y 

PROVIDER: S-EPMC8139006 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature