SNPs detection by eBWT positional clustering.

ABSTRACT:

Background

Sequencing technologies keep on turning cheaper and faster, thus putting a growing pressure for data structures designed to efficiently store raw data, and possibly perform analysis therein. In this view, there is a growing interest in alignment-free and reference-free variants calling methods that only make use of (suitably indexed) raw reads data.

Results

We develop the positional clustering theory that (i) describes how the extended Burrows-Wheeler Transform (eBWT) of a collection of reads tends to cluster together bases that cover the same genome position (ii) predicts the size of such clusters, and (iii) exhibits an elegant and precise LCP array based procedure to locate such clusters in the eBWT. Based on this theory, we designed and implemented an al

SUBMITTER: Prezza N 

PROVIDER: S-EPMC6364478 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature