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A method for the allocation of sequencing resources in genotyped livestock populations

Overview of attention for article published in Genetics Selection Evolution, May 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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Title
A method for the allocation of sequencing resources in genotyped livestock populations
Published in
Genetics Selection Evolution, May 2017
DOI 10.1186/s12711-017-0322-5
Pubmed ID
Authors

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

Abstract

This paper describes a method, called AlphaSeqOpt, for the allocation of sequencing resources in livestock populations with existing phased genomic data to maximise the ability to phase and impute sequenced haplotypes into the whole population. We present two algorithms. The first selects focal individuals that collectively represent the maximum possible portion of the haplotype diversity in the population. The second allocates a fixed sequencing budget among the families of focal individuals to enable phasing of their haplotypes at the sequence level. We tested the performance of the two algorithms in simulated pedigrees. For each pedigree, we evaluated the proportion of population haplotypes that are carried by the focal individuals and compared our results to a variant of the widely-used key ancestors approach and to two haplotype-based approaches. We calculated the expected phasing accuracy of the haplotypes of a focal individual at the sequence level given the proportion of the fixed sequencing budget allocated to its family. AlphaSeqOpt maximises the ability to capture and phase the most frequent haplotypes in a population in three ways. First, it selects focal individuals that collectively represent a larger portion of the population haplotype diversity than existing methods. Second, it selects focal individuals from across the pedigree whose haplotypes can be easily phased using family-based phasing and imputation algorithms, thus maximises the ability to impute sequence into the rest of the population. Third, it allocates more of the fixed sequencing budget to focal individuals whose haplotypes are more frequent in the population than to focal individuals whose haplotypes are less frequent. Unlike existing methods, we additionally present an algorithm to allocate part of the sequencing budget to the families (i.e. immediate ancestors) of focal individuals to ensure that their haplotypes can be phased at the sequence level, which is essential for enabling and maximising subsequent sequence imputation. We present a new method for the allocation of a fixed sequencing budget to focal individuals and their families such that the final sequenced haplotypes, when phased at the sequence level, represent the maximum possible portion of the haplotype diversity in the population that can be sequenced and phased at that budget.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 1 3%
Unknown 39 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 35%
Student > Ph. D. Student 7 18%
Student > Doctoral Student 5 13%
Student > Master 4 10%
Professor > Associate Professor 2 5%
Other 3 8%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 53%
Biochemistry, Genetics and Molecular Biology 6 15%
Veterinary Science and Veterinary Medicine 1 3%
Computer Science 1 3%
Psychology 1 3%
Other 1 3%
Unknown 9 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 May 2021.
All research outputs
#3,705,479
of 25,382,440 outputs
Outputs from Genetics Selection Evolution
#77
of 821 outputs
Outputs of similar age
#64,420
of 326,979 outputs
Outputs of similar age from Genetics Selection Evolution
#1
of 14 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 821 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,979 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.