Evidence map›Paper›PMID 24382753›Full record

ArticleGenetic epidemiology2014

A novel test for testing the optimally weighted combination of rare and common variants based on data of parents and affected children.

Qiuying Sha, Shuanglin Zhang

Abstract read
In one paragraph

Article in Genetic epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Qiuying ShaDepartment of Mathematical Sciences, Michigan Technological University, Houghton, Michigan, United States of America.
Shuanglin Zhang

Funding

GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
QUANTITATIVE TRAIT LOCUS MAPPING IN HUMAN PEDIGREESR01MH059490 · NIMH · SOUTHWEST FOUNDATION FOR BIOMEDICAL RES · PI BLANGERO, JOHN · 1998 to 2000
$426k
Statistical Methods for Family-Based Association StudiesR03HG006155 · NHGRI · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI SHA, QIUYING · 2012 to 2013
$156k
NHGRI NIH HHS R03 HG006155NIGMS NIH HHS R01 GM031575NIMH NIH HHS R01 MH059490
6 · The paper itself

Abstract

With the development of sequencing technologies, the direct testing of rare variant associations has become possible. Many statistical methods for detecting associations between rare variants and complex diseases have recently been developed, most of which are population-based methods for unrelated individuals. A limitation of population-based methods is that spurious associations can occur when there is a population structure. For rare variants, this problem can be more serious, because the spectrum of rare variation can be very different in diverse populations, as well as the current nonexistence of methods to control for population stratification in population-based rare variant associations. A solution to the problem of population stratification is to use family-based association tests, which use family members to control for population stratification. In this article, we propose a novel test for Testing the Optimally Weighted combination of variants based on data of Parents and Affected Children (TOW-PAC). TOW-PAC is a family-based association test that tests the combined effect of rare and common variants in a genomic region, and is robust to the directions of the effects of causal variants. Simulation studies confirm that, for rare variant associations, family-based association tests are robust to population stratification although population-based association tests can be seriously confounded by population stratification. The results of power comparisons show that the power of TOW-PAC increases with an increase of the number of affected children in each family and TOW-PAC based on multiple affected children per family is more powerful than TOW based on unrelated individuals.

Indexed as

Genetic Predisposition to DiseaseGenetic VariationChildComputer SimulationFemaleGenetics, PopulationGenome, HumanHumansMaleModels, GeneticParentsPedigreeassociation studiesfamily-based designoptimal weightsrare variants

Identifiers

PMID24382753
PMCPMC4162402

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.