↓ Skip to main content

Enriching rare variants using family-specific linkage information

Overview of attention for article published in BMC Proceedings, November 2011
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
22 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Enriching rare variants using family-specific linkage information
Published in
BMC Proceedings, November 2011
DOI 10.1186/1753-6561-5-s9-s82
Pubmed ID
Authors

Gang Shi, Jeannette Simino, Dabeeru C Rao

Abstract

Genome-wide association studies have been successful in identifying common variants for common complex traits in recent years. However, common variants have generally failed to explain substantial proportions of the trait heritabilities. Rare variants, structural variations, and gene-gene and gene-environment interactions, among others, have been suggested as potential sources of the so-called missing heritability. With the advent of exome-wide and whole-genome next-generation sequencing technologies, finding rare variants in functionally important sites (e.g., protein-coding regions) becomes feasible. We investigate the role of linkage information to select families enriched for rare variants using the simulated Genetic Analysis Workshop 17 data. In each replicate of simulated phenotypes Q1 and Q2 on 697 subjects in 8 extended pedigrees, we select one pedigree with the largest family-specific LOD score. Across all 200 replications, we compare the probability that rare causal alleles will be carried in the selected pedigree versus a randomly chosen pedigree. One example of successful enrichment was exhibited for gene VEGFC. The causal variant had minor allele frequency of 0.0717% in the simulated unrelated individuals and explained about 0.1% of the phenotypic variance. However, it explained 7.9% of the phenotypic variance in the eight simulated pedigrees and 23.8% in the family that carried the minor allele. The carrier's family was selected in all 200 replications. Thus our results show that family-specific linkage information is useful for selecting families for sequencing, thus ensuring that rare functional variants are segregating in the sequencing samples.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 14%
France 1 5%
Netherlands 1 5%
Sweden 1 5%
Korea, Republic of 1 5%
Unknown 15 68%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 41%
Student > Ph. D. Student 6 27%
Student > Master 2 9%
Professor > Associate Professor 2 9%
Student > Postgraduate 1 5%
Other 0 0%
Unknown 2 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 36%
Medicine and Dentistry 5 23%
Mathematics 2 9%
Biochemistry, Genetics and Molecular Biology 1 5%
Social Sciences 1 5%
Other 3 14%
Unknown 2 9%
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 2011.
All research outputs
#20,152,153
of 22,659,164 outputs
Outputs from BMC Proceedings
#318
of 374 outputs
Outputs of similar age
#218,507
of 240,147 outputs
Outputs of similar age from BMC Proceedings
#32
of 44 outputs
Altmetric has tracked 22,659,164 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 374 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 240,147 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.