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The Utility of Mitochondrial and Y Chromosome Phylogenetic Data to Improve Correction for Population Stratification

Overview of attention for article published in Frontiers in Genetics, January 2012
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Title
The Utility of Mitochondrial and Y Chromosome Phylogenetic Data to Improve Correction for Population Stratification
Published in
Frontiers in Genetics, January 2012
DOI 10.3389/fgene.2012.00301
Pubmed ID
Authors

Robert Makowsky, Qi Yan, Howard W. Wiener, Michael Sandel, Brahim Aissani, Hemant K. Tiwari, Sadeep Shrestha

Abstract

Genome-wide association (GWA) studies have become a standard approach for discovering and validating genomic polymorphisms putatively associated with phenotypes of interest. Accounting for population structure in GWA studies is critical to attain unbiased parameter measurements and control Type I error. One common approach to accounting for population structure is to include several principal components derived from the entire autosomal dataset, which reflects population structure signal. However, knowing which components to include is subjective and generally not conclusive. We examined how phylogenetic signal from mitochondrial DNA (mtDNA) and chromosome Y (chr:Y) markers is concordant with principal component data based on autosomal markers to determine whether mtDNA and chr:Y phylogenetic data can help guide principal component selection. Using HAPMAP and other original data from individuals of multiple ancestries, we examined the relationships of mtDNA and chr:Y phylogenetic signal with the autosomal PCA using best subset logistic regression. We show that while the two approaches agree at times, this is independent of the component order and not completely represented in the Eigen values. Additionally, we use simulations to demonstrate that our approach leads to a slightly reduced Type I error rate compared to the standard approach. This approach provides preliminary evidence to support the theoretical concept that mtDNA and chr:Y data can be informative in locating the PCs that are most associated with evolutionary history of populations that are being studied, although the utility of such information will depend on the specific situation.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ireland 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 42%
Student > Ph. D. Student 5 21%
Student > Doctoral Student 3 13%
Student > Master 3 13%
Student > Bachelor 2 8%
Other 2 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 54%
Biochemistry, Genetics and Molecular Biology 6 25%
Linguistics 1 4%
Arts and Humanities 1 4%
Computer Science 1 4%
Other 1 4%
Unknown 1 4%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 December 2012.
All research outputs
#20,176,348
of 22,689,790 outputs
Outputs from Frontiers in Genetics
#8,521
of 11,754 outputs
Outputs of similar age
#221,229
of 244,142 outputs
Outputs of similar age from Frontiers in Genetics
#195
of 255 outputs
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