μ- PBWT: a lightweight r-indexing of the PBWT for storing and querying UK Biobank data

Author:

Cozzi Davide1ORCID,Rossi Massimiliano2,Rubinacci Simone3ORCID,Gagie Travis4ORCID,Köppl Dominik56,Boucher Christina2,Bonizzoni Paola1ORCID

Affiliation:

1. Department of Informatics, Systems and Communication, University of Milano-Bicocca , Milan 20126, Italy

2. Department of Computer & Information Science & Engineering, Herbert-Wertheim College of Engineering, University of Florida , Gainesville, Florida 32611, United States

3. Department of Computational Biology, University of Lausanne , Lausanne 1015, Switzerland

4. Faculty of Computer Science, Dalhousie University , Halifax B3H 4R2, Canada

5. M&D Data Science Center, Tokyo Medical and Dental University , Tokyo 113-8510, Japan

6. Department of Computer Science, University of Muenster , Muenster 48149, Germany

Abstract

Abstract Motivation The Positional Burrows–Wheeler Transform (PBWT) is a data structure that indexes haplotype sequences in a manner that enables finding maximal haplotype matches in h sequences containing w variation sites in O(hw) time. This represents a significant improvement over classical quadratic-time approaches. However, the original PBWT data structure does not allow for queries over Biobank panels that consist of several millions of haplotypes, if an index of the haplotypes must be kept entirely in memory. Results In this article, we leverage the notion of r-index proposed for the BWT to present a memory-efficient method for constructing and storing the run-length encoded PBWT, and computing set maximal matches (SMEMs) queries in haplotype sequences. We implement our method, which we refer to as μ-PBWT, and evaluate it on datasets of 1000 Genome Project and UK Biobank data. Our experiments demonstrate that the μ-PBWT reduces the memory usage up to a factor of 20% compared to the best current PBWT-based indexing. In particular, μ-PBWT produces an index that stores high-coverage whole genome sequencing data of chromosome 20 in about a third of the space of its BCF file. μ-PBWT is an adaptation of techniques for the run-length compressed BWT for the PBWT (RLPBWT) and it is based on keeping in memory only a succinct representation of the RLPBWT that still allows the efficient computation of set maximal matches (SMEMs) over the original panel. Availability and implementation Our implementation is open source and available at https://github.com/dlcgold/muPBWT. The binary is available at https://bioconda.github.io/recipes/mupbwt/README.html.

Funder

National Science Foundation

European Union’s Horizon 2020 ITN programme

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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