Efficient Construction of a Complete Index for Pan-Genomics Read Alignment

Alan Kuhnle, Taher Mun, Christina Boucher, Travis Gagie, Ben Langmead, Giovanni Manzini

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Abstract

While short read aligners, which predominantly use the FM-index, are able to easily index one or a few human genomes, they do not scale well to indexing databases containing thousands of genomes. To understand why, it helps to examine the main components of the FM-index in more detail, which is a rank data structure over the Burrows-Wheeler Transform (BWT ) of the string that will allow us to find the interval in the string’s suffix array (SA ) containing pointers to starting positions of occurrences of a given pattern; second, a sample of the SA that—when used with the rank data structure—allows us access to the SA. The rank data structure can be kept small even for large genomic databases, by run-length compressing the BWT, but until recently there was no means known to keep the SA sample small without greatly slowing down access to the SA. Now that Gagie et al. (SODA 2018) have defined an SA sample that takes about the same space as the run-length compressed BWT —we have the design for efficient FM-indexes of genomic databases but are faced with the problem of building them. In 2018 we showed how to build the BWT of large genomic databases efficiently (WABI 2018) but the problem of building Gagie et al.’s SA sample efficiently was left open. We compare our approach to state-of-the-art methods for constructing the SA sample, and demonstrate that it is the fastest and most space-efficient method on highly repetitive genomic databases. Lastly, we apply our method for indexing partial and whole human genomes and show that it improves over Bowtie with respect to both memory and time. Availability: The implementations of our methods can be found at https://gitlab.com/manzai/Big-BWT (BWT and SA sample construction) and at https://github.com/alshai/r-index (indexing).

Lingua originaleInglese
Titolo della pubblicazione ospiteResearch in Computational Molecular Biology - 23rd Annual International Conference, RECOMB 2019, Proceedings
EditorLenore J. Cowen
EditoreSpringer Verlag
Pagine158-173
Numero di pagine16
ISBN (stampa)9783030170820
DOI
Stato di pubblicazionePubblicato - 2019
Pubblicato esternamente
Evento23rd International Conference on Research in Computational Molecular Biology, RECOMB 2019 - Washington, United States
Durata: 5 mag 20198 mag 2019

Serie di pubblicazioni

NomeLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11467 LNBI
ISSN (stampa)0302-9743
ISSN (elettronico)1611-3349

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???event.eventtypes.event.conference???23rd International Conference on Research in Computational Molecular Biology, RECOMB 2019
Paese/TerritorioUnited States
CittàWashington
Periodo5/05/198/05/19

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