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PMID: 29373581 Published · epublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

MUMmer4: A fast and versatile genome alignment system.

PLoS computational biology ·Vol. 14 ·No. 1 ·2018-00-00 ·Pages e1005944

Marçais G, Delcher AL, Phillippy AM, Coston R, Salzberg SL, Zimin A

Abstract

The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes; we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available.

MeSH Terms
Algorithms Animals Arabidopsis/genetics Computational Biology/methods Genome, Human Genome, Plant Genomics Humans Models, Theoretical Pan troglodytes Polymorphism, Single Nucleotide Programming Languages Sequence Alignment/methods Sequence Analysis, DNA Sequence Analysis, Protein Software
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Marçais Guillaume ORCID
Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, United States of America. | Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
Delcher Arthur L
Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.
Phillippy Adam M
National Human Genome Research Institute, Bethesda, Maryland, United States of America.
Coston Rachel
Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.
Salzberg Steven L
Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America. | Departments of Biomedical Engineering, Computer Science, and Biostatistics, Johns Hopkins University, Baltimore, Maryland, United States of America.
Zimin Aleksey ORCID
Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, United States of America. | Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.
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Article Info
Journal
PLoS computational biology
Abbr.
PLoS Comput Biol
ISSN
1553-7358
Published
2018-00-00
Epub
2018-00-26
Pages
e1005944
Language
English
Region
United States
NLM ID
101238922
PMCID
PMC5802927
Subset
IM
Grants
NIGMS NIH HHS · R01 GM083873 · United States
NHGRI NIH HHS · R01 HG006677 · United States
NIGMS NIH HHS · R35 GM130151 · United States
NIH HHS · R01 GM083873 · United States
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