AGC: compact representation of assembled genomes with fast queries and updates

Author:

Deorowicz Sebastian1ORCID,Danek Agnieszka1ORCID,Li Heng23ORCID

Affiliation:

1. Department of Algorithmics and Software, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology , Akademicka 16 , Gliwice 44-100, Poland

2. Department of Data Sciences, Dana-Farber Cancer Institute , Boston, MA 02215, USA

3. Department of Biomedical Informatics, Harvard Medical School , Boston, MA 02115, USA

Abstract

AbstractMotivationHigh-quality sequence assembly is the ultimate representation of complete genetic information of an individual. Several ongoing pangenome projects are producing collections of high-quality assemblies of various species. Each project has already generated assemblies of hundreds of gigabytes on disk, greatly impeding the distribution of and access to such rich datasets.ResultsHere, we show how to reduce the size of the sequenced genomes by 2–3 orders of magnitude. Our tool compresses the genomes significantly better than the existing programs and is much faster. Moreover, its unique feature is the ability to access any contig (or its part) in a fraction of a second and easily append new samples to the compressed collections. Thanks to this, AGC could be useful not only for backup or transfer purposes but also for routine analysis of pangenome sequences in common pipelines. With the rapidly reduced cost and improved accuracy of sequencing technologies, we anticipate more comprehensive pangenome projects with much larger sample sizes. AGC is likely to become a foundation tool to store, distribute and access pangenome data.Availability and implementationThe source code of AGC is available at https://github.com/refresh-bio/agc. The package can be installed via Bioconda at https://anaconda.org/bioconda/agc.Supplementary informationSupplementary data are available at Bioinformatics online.

Funder

National Science Centre

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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