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dc.contributor.authorRos Freixedes, Roger
dc.contributor.authorGonen, Serap
dc.contributor.authorGorjanc, Gregor
dc.contributor.authorHickey, John M.
dc.date.accessioned2020-02-05T07:48:19Z
dc.date.available2020-02-05T07:48:19Z
dc.date.issued2017-10-25
dc.identifier.issn0999-193X
dc.identifier.urihttp://hdl.handle.net/10459.1/67938
dc.description.abstractBackground: This paper describes a heuristic method for allocating low-coverage sequencing resources by target- ing haplotypes rather than individuals. Low-coverage sequencing assembles high-coverage sequence information for every individual by accumulating data from the genome segments that they share with many other individuals into consensus haplotypes. Deriving the consensus haplotypes accurately is critical for achieving a high phasing and imputation accuracy. In order to enable accurate phasing and imputation of sequence information for the whole population, we allocate the available sequencing resources among individuals with existing phased genomic data by targeting the sequencing coverage of their haplotypes. Results: Our method, called AlphaSeqOpt, prioritizes haplotypes using a score function that is based on the fre- quency of the haplotypes in the sequencing set relative to the target coverage. AlphaSeqOpt has two steps: (1) selec- tion of an initial set of individuals by iteratively choosing the individuals that have the maximum score conditional on the current set, and (2) refinement of the set through several rounds of exchanges of individuals. AlphaSeqOpt is very effective for distributing a fixed amount of sequencing resources evenly across haplotypes, which results in a reduction of the proportion of haplotypes that are sequenced below the target coverage. AlphaSeqOpt can provide a greater proportion of haplotypes sequenced at the target coverage by sequencing less individuals, as compared with other methods that use a score function based on haplotype frequencies in the population. A refinement of the initially selected set can provide a larger more diverse set with more unique individuals, which is beneficial in the context of low-coverage sequencing. We extend the method with an approach for filtering rare haplotypes based on their flanking haplotypes, so that only those that are likely to derive from a recombination event are targeted. Conclusions: We present a method for allocating sequencing resources so that a greater proportion of haplotypes are sequenced at a coverage that is sufficiently high for population-based imputation with low-coverage sequencing. The haplotype score function, the refinement step, and the new approach for filtering rare haplotypes make AlphaSe- qOpt more effective for that purpose than previously reported methods for reducing sequencing redundancy.
dc.description.sponsorshipThe authors acknowledge the financial support from the BBSRC ISPG to The Roslin Institute BB/J004235/1, from Genus PLC and from Grant Nos. BB/M009254/1, BB/L020726/1, BB/N004736/1, BB/N004728/1, BB/L020467/1, BB/N006178/1 and Medical Research Council (MRC) Grant No. MR/M000370/1. This work has made use of the resources provided by the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk).
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherBMC (part of Springer Nature)
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1186/s12711-017-0353-y
dc.relation.ispartofGenetics Selection Evolution, 2017, vol. 49, article number 78
dc.rightscc-by (c) Ros Freixedes, Roger et al., 2017
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleA method for allocating low-coverage sequencing resources by targeting haplotypes rather than individuals
dc.typeinfo:eu-repo/semantics/article
dc.date.updated2020-02-05T07:48:19Z
dc.identifier.idgrec029237
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1186/s12711-017-0353-y


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cc-by (c) Ros Freixedes, Roger et al., 2017
Except where otherwise noted, this item's license is described as cc-by (c) Ros Freixedes, Roger et al., 2017