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On Estimation of Genome Composition in Genetically Admixed Individuals Using Constrained Genomic Regression

Overview of attention for article published in Frontiers in Genetics, May 2018
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Title
On Estimation of Genome Composition in Genetically Admixed Individuals Using Constrained Genomic Regression
Published in
Frontiers in Genetics, May 2018
DOI 10.3389/fgene.2018.00185
Pubmed ID
Authors

Vinzent Boerner, Dörte Wittenburg

Abstract

Quantifying the population stratification in genotype samples has become a standard procedure for data manipulation before conducting genome wide association studies, as well as for tracing patterns of migration in humans and animals, and for inference about extinct founder populations. The most widely used approach capable of providing biologically interpretable results is a likelihood formulation which allows for estimation of founder genome proportions and founder allele frequency conditional on the observed genotypes. However, if founder allele frequencies are known and samples are dominated by admixed genotypes this approach may lead to biased inference. In addition, processing time increases drastically with the number of genetic markers. This article describes a simplified approach for obtaining biologically meaningful measures of population stratification at the genotype level conditional on known founder allele frequencies. It was tested on cattle and human data sets with 4,022 and 150,000 genetic markers, respectively, and proved to be very accurate in situations where founder poplations were correctly specified, or under-, over-, and miss-specified. Moreover, processing time was only marginally affected by an increase in the number of markers.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 29%
Lecturer 2 29%
Student > Master 2 29%
Unknown 1 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 57%
Medicine and Dentistry 1 14%
Unknown 2 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 13 October 2018.
All research outputs
#14,646,643
of 25,163,238 outputs
Outputs from Frontiers in Genetics
#3,270
of 13,545 outputs
Outputs of similar age
#171,204
of 337,946 outputs
Outputs of similar age from Frontiers in Genetics
#55
of 128 outputs
Altmetric has tracked 25,163,238 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,545 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done well, scoring higher than 75% 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 337,946 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.