Lep-MAP3 : robust linkage mapping even for low-coverage whole genome sequencing data

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dc.contributor.author Rastas, Pasi
dc.date.accessioned 2020-02-21T12:29:01Z
dc.date.available 2020-02-21T12:29:01Z
dc.date.issued 2017-12-01
dc.identifier.citation Rastas , P 2017 , ' Lep-MAP3 : robust linkage mapping even for low-coverage whole genome sequencing data ' , Bioinformatics , vol. 33 , no. 23 , pp. 3726-3732 . https://doi.org/10.1093/bioinformatics/btx494
dc.identifier.other PURE: 95654581
dc.identifier.other PURE UUID: 34f432b8-e16d-43d2-87bd-85e0fef9b5c7
dc.identifier.other WOS: 000417004100006
dc.identifier.other Scopus: 85042091187
dc.identifier.uri http://hdl.handle.net/10138/312091
dc.description.abstract Motivation: Accurate and dense linkage maps are useful in family-based linkage and association studies, quantitative trait locus mapping, analysis of genome synteny and other genomic data analyses. Moreover, linkage mapping is one of the best ways to detect errors in de novo genome assemblies, as well as to orient and place assembly contigs within chromosomes. A small mapping cross of tens of individuals will detect many errors where distant parts of the genome are erroneously joined together. With more individuals and markers, even more local errors can be detected and more contigs can be oriented. However, the tools that are currently available for constructing linkage maps are not well suited for large, possible low-coverage, whole genome sequencing datasets. Results: Here we present a linkage mapping software Lep-MAP3, capable of mapping high-throughput whole genome sequencing datasets. Such data allows cost-efficient genotyping of millions of single nucleotide polymorphisms (SNPs) for thousands of individual samples, enabling, among other analyses, comprehensive validation and refinement of de novo genome assemblies. The algorithms of Lep-MAP3 can analyse low-coverage datasets and reduce data filtering and curation on any data. This yields more markers in the final maps with less manual work even on problematic datasets. We demonstrate that Lep-MAP3 obtains very good performance already on 5x sequencing coverage and outperforms the fastest available software on simulated data on accuracy and often on speed. We also construct de novo linkage maps on 7-12x whole-genome data on the Red postman butterfly (Heliconius erato) with almost 3 million markers. en
dc.format.extent 7
dc.language.iso eng
dc.relation.ispartof Bioinformatics
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject MAPS
dc.subject FAMILY
dc.subject TOOLS
dc.subject 1182 Biochemistry, cell and molecular biology
dc.subject 111 Mathematics
dc.subject 113 Computer and information sciences
dc.title Lep-MAP3 : robust linkage mapping even for low-coverage whole genome sequencing data en
dc.type Article
dc.contributor.organization Biosciences
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1093/bioinformatics/btx494
dc.relation.issn 1367-4803
dc.rights.accesslevel openAccess
dc.type.version acceptedVersion

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