Evidence map›Paper›PMID 29070022›Full record

ArticleGenetics, selection, evolution : GSE2017

A method for allocating low-coverage sequencing resources by targeting haplotypes rather than individuals.

Roger Ros-Freixedes, Serap Gonen, Gregor Gorjanc, John M Hickey

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

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  17. Haplotype structure in commercial maize breeding programs in relation to key founder lines.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Roger Ros-FreixedesThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.ORCID 0000-0002-3745-6736
Serap GonenThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.ORCID 0000-0002-3937-6473
Gregor GorjancThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.ORCID 0000-0001-8008-2787
John M HickeyThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. john.hickey@roslin.ed.ac.uk.ORCID 0000-0001-5675-3974

Funding

Biotechnology and Biological Sciences Research Council BB/J004235/1Biotechnology and Biological Sciences Research Council BB/L020467/1Biotechnology and Biological Sciences Research Council BB/L020726/1Biotechnology and Biological Sciences Research Council BB/M009254/1Biotechnology and Biological Sciences Research Council BB/N004728/1Biotechnology and Biological Sciences Research Council BB/N004736/1Biotechnology and Biological Sciences Research Council BB/N006178/1Medical Research Council MR/M000370/1
6 · The paper itself

Abstract

backgroundThis paper describes a heuristic method for allocating low-coverage sequencing resources by targeting 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.

resultsOur method, called AlphaSeqOpt, prioritizes haplotypes using a score function that is based on the frequency of the haplotypes in the sequencing set relative to the target coverage. AlphaSeqOpt has two steps: (1) selection 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.

conclusionsWe 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 AlphaSeqOpt more effective for that purpose than previously reported methods for reducing sequencing redundancy.

Indexed as

AlgorithmsHaplotypesAnimalsCattleDatasets as TopicGenome-Wide Association StudyModels, GeneticSequence Analysis, DNA

Identifiers

PMID29070022
PMCPMC5655873

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.