FARVAT: a family-based rare variant association test

Sungkyoung Choi; Sungyoung Lee; Sven Cichon; Markus M Nöthen; Christoph Lange; Taesung Park; Sungho Won

doi:10.1093/bioinformatics/btu496

FARVAT: a family-based rare variant association test

Bioinformatics. 2014 Nov 15;30(22):3197-205. doi: 10.1093/bioinformatics/btu496. Epub 2014 Jul 29.

Authors

Sungkyoung Choi¹, Sungyoung Lee¹, Sven Cichon¹, Markus M Nöthen¹, Christoph Lange¹, Taesung Park², Sungho Won¹

Affiliations

¹ Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.
² Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea Interdisciplinary Program in bioinformatics, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea, Institute of Human Genetics, University of Bonn, D-53127 Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue. Boston, MA 02115, USA, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA, Center for Genomic Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston MA 02115, USA, Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA, Institute for Genomic Mathematics, University of Bonn, D-53127 Bonn, Germany, German Center for Neurodegenerative Diseases, D-53127 Bonn, Germany, Department of Statistics, Seoul National University 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea and Department of Public Health Science, Seoul National University, 1 Kwanak-ro Kwanak-gu, Seoul 151-742, Korea.

PMID: 25075118
DOI: 10.1093/bioinformatics/btu496

Abstract

Motivation: 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.

Results: 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.

Availability: The software calculates various statistics for the analysis of related samples, and it is freely downloadable from http://healthstats.snu.ac.kr/software/farvat.

Contact: won1@snu.ac.kr or tspark@stats.snu.ac.kr

Supplementary information: supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Family
Genetic Association Studies / methods*
Genetic Variation*
Humans
Schizophrenia / genetics
Software