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@ARTICLE{Choi:137632,
author = {Choi, Sungkyoung and Lee, Sungyoung and Cichon, Sven and
Nöthen, Markus M and Lange, Christoph and Park, Taesung and
Won, Sungho},
title = {{FARVAT}: a family-based rare variant association test.},
journal = {Bioinformatics},
volume = {30},
number = {22},
issn = {1460-2059},
address = {Oxford},
publisher = {Oxford Univ. Press},
reportid = {DZNE-2020-03954},
pages = {3197-3205},
year = {2014},
abstract = {Individuals in each family are genetically more homogeneous
than unrelated individuals, and family-based designs are
often recommended for the analysis of rare variants.
However, despite the importance of family-based samples
analysis, few statistical methods for rare variant
association analysis are available.In this report, we
propose a FAmily-based Rare Variant Association Test
(FARVAT). FARVAT is based on the quasi-likelihood of whole
families, and is statistically and computationally efficient
for the extended families. FARVAT assumed that families were
ascertained with the disease status of family members, and
incorporation of the estimated genetic relationship matrix
to the proposed method provided robustness under the
presence of the population substructure. Depending on the
choice of working matrix, our method could be a burden test
or a variance component test, and could be extended to the
SKAT-O-type statistic. FARVAT was implemented in C++, and
application of the proposed method to schizophrenia data and
simulated data for GAW17 illustrated its practical
importance.The software calculates various statistics for
the analysis of related samples, and it is freely
downloadable from
http://healthstats.snu.ac.kr/software/farvat.won1@snu.ac.kr
or tspark@stats.snu.ac.krsupplementary data are available at
Bioinformatics online.},
keywords = {Family / Genetic Association Studies: methods / Genetic
Variation / Humans / Schizophrenia: genetics / Software},
cin = {U T4 Researchers - Bonn},
ddc = {570},
cid = {I:(DE-2719)7000008},
pnm = {345 - Population Studies and Genetics (POF3-345)},
pid = {G:(DE-HGF)POF3-345},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:25075118},
doi = {10.1093/bioinformatics/btu496},
url = {https://pub.dzne.de/record/137632},
}