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Successful identification of rare variants using oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies

Overview of attention for article published in BMC Proceedings, November 2011
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Title
Successful identification of rare variants using oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies
Published in
BMC Proceedings, November 2011
DOI 10.1186/1753-6561-5-s9-s11
Pubmed ID
Authors

France Gagnon, Nicole M Roslin, Mathieu Lemire

Abstract

We aim to identify rare variants that have large effects on trait variance using a cost-efficient strategy. We use an oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies to identify families more likely to harbor rare variants, by estimating the mean number of quantitative trait loci (QTLs) in each family. We hypothesize that families with additional QTLs, relative to the other families, are more likely to segregate functional rare variants. We test the association of rare variants with the traits only in regions where at least modest evidence of linkage with the trait is observed, thereby reducing the number of tests performed. We found that family 7 harbored an estimated two, one, and zero additional QTLs for traits Q1, Q2, and Q4, respectively. Two rare variants (C4S4935 and C6S2981) segregating in family 7 were associated with Q1 and explained a substantial proportion of the observed linkage signal. These rare variants have 31 and 22 carriers, respectively, in the 128-member family and entered through a single but different founder. For Q2, we found one rare variant unique to family 7 that showed small effect and weak evidence of association; this was a false positive. These results are a proof of principle that prioritizing the sequencing of carefully selected extended families is a simple and cost-efficient design strategy for sequencing studies aiming at identifying functional rare variants.

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Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 6%
Sweden 1 6%
Unknown 15 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 41%
Student > Ph. D. Student 6 35%
Professor 1 6%
Other 1 6%
Student > Master 1 6%
Other 1 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 59%
Medicine and Dentistry 3 18%
Biochemistry, Genetics and Molecular Biology 2 12%
Mathematics 2 12%
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 09 December 2013.
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#18,355,685
of 22,733,113 outputs
Outputs from BMC Proceedings
#265
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Outputs of similar age
#196,118
of 240,335 outputs
Outputs of similar age from BMC Proceedings
#23
of 44 outputs
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