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Genet Epidemiol. 2016 Sep;40(6):502-11. doi: 10.1002/gepi.21985. Epub 2016 Jun 17.

Family-Based Rare Variant Association Analysis: A Fast and Efficient Method of Multivariate Phenotype Association Analysis.

Author information

  • 1Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea.
  • 2Institute of Health and Environment, Seoul National University, Seoul, Korea.
  • 3Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.
  • 4Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
  • 5Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
  • 6Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
  • 7Graduate School of Public Health, Seoul National University, Seoul, Korea.

Abstract

Family-based designs have been repeatedly shown to be powerful in detecting the significant rare variants associated with human diseases. Furthermore, human diseases are often defined by the outcomes of multiple phenotypes, and thus we expect multivariate family-based analyses may be very efficient in detecting associations with rare variants. However, few statistical methods implementing this strategy have been developed for family-based designs. In this report, we describe one such implementation: the multivariate family-based rare variant association tool (mFARVAT). mFARVAT is a quasi-likelihood-based score test for rare variant association analysis with multiple phenotypes, and tests both homogeneous and heterogeneous effects of each variant on multiple phenotypes. Simulation results show that the proposed method is generally robust and efficient for various disease models, and we identify some promising candidate genes associated with chronic obstructive pulmonary disease. The software of mFARVAT is freely available at http://healthstat.snu.ac.kr/software/mfarvat/, implemented in C++ and supported on Linux and MS Windows.

KEYWORDS:

association analysis; family-based design; multivariate phenotypes; rare variants

PMID:
27312886
PMCID:
PMC4981535
[Available on 2017-09-01]
DOI:
10.1002/gepi.21985
[PubMed - in process]
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