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

Dolle, D. D., Liu, Z., Cotten, M. , Simpson, J. T., Iqbal, Z., Durbin, R., McCarthy, S. A. and Jeabe, T. M. (2017) Using reference-free compressed data structures to analyze sequencing reads from thousands of human genomes. Genome Research, 27(2), pp. 300-309. (doi: 10.1101/gr.211748.116) (PMID:27986821) (PMCID:PMC5287235)

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 becomes more efficient. We assess the support in the 1000 Genomes read data for every base position of two human reference assembly versions, identifying that 3.2 Mbp with population support was lost in the transition from GRCh37 with 13.7 Mbp added to GRCh38. We show that the vast majority of variant alleles can be uniquely described by overlapping 31-mers and show how rapid and accurate SNP and indel genotyping can be carried out across the genomes in the population BWT. We use the population BWT to carry out nonreference queries to search for the presence of all known viral genomes and discover human T-lymphotropic virus 1 integrations in six samples in a recognized epidemiological distribution.

• Item Type: Articles
• Additional Information: This work was supported by the Wellcome Trust.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Cotten, Professor Matthew
• Authors: Dolle, D. D., Liu, Z., Cotten, M., Simpson, J. T., Iqbal, Z., Durbin, R., McCarthy, S. A., and Jeabe, T. M.
• College/School: College of Medical Veterinary and Life Sciences > School of Infection & Immunity; College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research
• Journal Name: Genome Research
• Publisher: Cold Spring Harbor Laboratory
• ISSN: 1088-9051
• ISSN (Online): 1549-5469
• Published Online: 16 December 2016
• Copyright Holders: Copyright © 2017 Dolle et al.
• First Published: First published in Genome Research 27(2): 300-309
• Publisher Policy: Reproduced under a Creative Commons License