Using reference-free compressed data structures to analyze sequencing reads from thousands of human genomes.

ABSTRACT: We are rapidly approaching the point where we have sequenced millions of human genomes. There is a pressing need for new data structures to store raw sequencing data and efficient algorithms for population scale analysis. Current reference-based data formats do not fully exploit the redundancy in population sequencing nor take advantage of shared genetic variation. In recent years, the Burrows-Wheeler transform (BWT) and FM-index have been widely employed as a full-text searchable index for read alignment and de novo assembly. We introduce the concept of a population BWT and use it to store and index the sequencing reads of 2705 samples from the 1000 Genomes Project. A key feature is that, as more genomes are added, identical read sequences are increasingly observed, and compression become

SUBMITTER: Dolle DD 

PROVIDER: S-EPMC5287235 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature