FARVAT: a family-based rare variant association test

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.

[1]  Christoph Lange,et al.  Power calculations for a general class of family-based association tests: dichotomous traits. , 2002, American journal of human genetics.

[2]  Gang Shi,et al.  Optimum designs for next‐generation sequencing to discover rare variants for common complex disease , 2011, Genetic epidemiology.

[3]  Kathryn Roeder,et al.  Testing for an Unusual Distribution of Rare Variants , 2011, PLoS genetics.

[4]  Iuliana Ionita-Laza,et al.  A New Testing Strategy to Identify Rare Variants with Either Risk or Protective Effect on Disease , 2011, PLoS genetics.

[5]  Momiao Xiong,et al.  Family-based association studies for next-generation sequencing. , 2012, American journal of human genetics.

[6]  W. G. Hill,et al.  Genome partitioning of genetic variation for complex traits using common SNPs , 2011, Nature Genetics.

[7]  Claudia Hemmelmann,et al.  Statistical analysis of rare sequence variants: an overview of collapsing methods , 2011, Genetic epidemiology.

[8]  Juan Manuel Peralta,et al.  Genetic Analysis Workshop 17 mini-exome simulation , 2011, BMC proceedings.

[9]  Scott T. Weiss,et al.  A New Powerful Non-Parametric Two-Stage Approach for Testing Multiple Phenotypes in Family-Based Association Studies , 2003, Human Heredity.

[10]  M. Rieder,et al.  Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies. , 2012, American journal of human genetics.

[11]  T. Thornton,et al.  Case-control association testing with related individuals: a more powerful quasi-likelihood score test. , 2007, American journal of human genetics.

[12]  Jay Shendure,et al.  Rare-variant extensions of the transmission disequilibrium test: application to autism exome sequence data. , 2014, American journal of human genetics.

[13]  Pablo Cingolani,et al.  © 2012 Landes Bioscience. Do not distribute. , 2022 .

[14]  Xihong Lin,et al.  Rare-variant association testing for sequencing data with the sequence kernel association test. , 2011, American journal of human genetics.

[15]  A. Piazza,et al.  Human Genomic Diversity in Europe: A Summary of Recent Research and Prospects for the Future , 1993, European journal of human genetics : EJHG.

[16]  Christoph Lange,et al.  Genomic screening and replication using the same data set in family-based association testing , 2005, Nature Genetics.

[17]  Scott T. Weiss,et al.  On the Analysis of Genome-Wide Association Studies in Family-Based Designs: A Universal, Robust Analysis Approach and an Application to Four Genome-Wide Association Studies , 2009, PLoS genetics.

[18]  R. Elston,et al.  The power of independent types of genetic information to detect association in a case‐control study design , 2008, Genetic epidemiology.

[19]  T. Thornton,et al.  XM: Association Testing on the X‐Chromosome in Case‐Control Samples With Related Individuals , 2012, Genetic epidemiology.

[20]  S. Leal,et al.  Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. , 2008, American journal of human genetics.

[21]  Lee-Jen Wei,et al.  Pooled Association Tests for Rare Variants in Exon-Resequencing Studies , 2010 .

[22]  S. Gabriel,et al.  Calibrating a coalescent simulation of human genome sequence variation. , 2005, Genome research.

[23]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[24]  Iuliana Ionita-Laza,et al.  Rare Variant Analysis for Family-Based Design , 2013, PloS one.

[25]  W. Ewens,et al.  Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). , 1993, American journal of human genetics.

[26]  Mary Sara McPeek,et al.  ROADTRIPS: case-control association testing with partially or completely unknown population and pedigree structure. , 2010, American journal of human genetics.

[27]  Iuliana Ionita-Laza,et al.  Family-based association tests for sequence data, and comparisons with population-based association tests , 2013, European Journal of Human Genetics.

[28]  Mary Sara McPeek,et al.  Best Linear Unbiased Allele‐Frequency Estimation in Complex Pedigrees , 2004, Biometrics.

[29]  D. Reich,et al.  Principal components analysis corrects for stratification in genome-wide association studies , 2006, Nature Genetics.

[30]  Xin Xu,et al.  Implementing a unified approach to family‐based tests of association , 2000, Genetic epidemiology.

[31]  D. Balding,et al.  A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity , 2005, Genetica.

[32]  Christoph Lange,et al.  A general framework for robust and efficient association analysis in family‐based designs: quantitative and dichotomous phenotypes , 2013, Statistics in medicine.

[33]  Judy H. Cho,et al.  Finding the missing heritability of complex diseases , 2009, Nature.

[34]  Xihong Lin,et al.  Optimal tests for rare variant effects in sequencing association studies. , 2012, Biostatistics.

[35]  Huan Liu,et al.  A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables , 2009, Comput. Stat. Data Anal..