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Article: OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps

TitleOMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
Authors
Keywordscomparative genomics
copy number variation
haplotypes
optical mapping
single-molecule analysis
Issue Date2019
PublisherOxford University Press (OUP): Policy C. The Journal's web site is located at https://academic.oup.com/gigascience
Citation
GigaScience, 2019, v. 8 n. 7, p. article no. giz079 How to Cite?
AbstractBACKGROUND: Optical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples. FINDINGS: We present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains. CONCLUSIONS: With the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools.
Persistent Identifierhttp://hdl.handle.net/10722/293157
ISSN
2019 Impact Factor: 5.993
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLeung, AKY-
dc.contributor.authorLiu, MCJ-
dc.contributor.authorLi, L-
dc.contributor.authorLai, YYY-
dc.contributor.authorChu, C-
dc.contributor.authorKwok, PY-
dc.contributor.authorHo, PL-
dc.contributor.authorYip, KY-
dc.contributor.authorChan, TF-
dc.date.accessioned2020-11-23T08:12:38Z-
dc.date.available2020-11-23T08:12:38Z-
dc.date.issued2019-
dc.identifier.citationGigaScience, 2019, v. 8 n. 7, p. article no. giz079-
dc.identifier.issn2047-217X-
dc.identifier.urihttp://hdl.handle.net/10722/293157-
dc.description.abstractBACKGROUND: Optical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples. FINDINGS: We present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains. CONCLUSIONS: With the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools.-
dc.languageeng-
dc.publisherOxford University Press (OUP): Policy C. The Journal's web site is located at https://academic.oup.com/gigascience-
dc.relation.ispartofGigaScience-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectcomparative genomics-
dc.subjectcopy number variation-
dc.subjecthaplotypes-
dc.subjectoptical mapping-
dc.subjectsingle-molecule analysis-
dc.titleOMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps-
dc.typeArticle-
dc.identifier.emailHo, PL: plho@hku.hk-
dc.identifier.authorityHo, PL=rp00406-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1093/gigascience/giz079-
dc.identifier.pmid31289833-
dc.identifier.pmcidPMC6615982-
dc.identifier.scopuseid_2-s2.0-85069318796-
dc.identifier.hkuros319286-
dc.identifier.volume8-
dc.identifier.issue7-
dc.identifier.spagearticle no. giz079-
dc.identifier.epagearticle no. giz079-
dc.identifier.isiWOS:000482312700004-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl2047-217X-

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