Journal Article DZNE-2020-03954

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FARVAT: a family-based rare variant association test.

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2014
Oxford Univ. Press Oxford

Bioinformatics 30(22), 3197-3205 () [10.1093/bioinformatics/btu496]

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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.

Keyword(s): Family (MeSH) ; Genetic Association Studies: methods (MeSH) ; Genetic Variation (MeSH) ; Humans (MeSH) ; Schizophrenia: genetics (MeSH) ; Software (MeSH)

Classification:

Contributing Institute(s):
  1. U T4 Researchers - Bonn (U T4 Researchers - Bonn)
Research Program(s):
  1. 345 - Population Studies and Genetics (POF3-345) (POF3-345)

Appears in the scientific report 2014
Database coverage:
Medline ; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; NationallizenzNationallizenz ; PubMed Central ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection
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 Record created 2020-02-18, last modified 2024-03-21



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