An improved robust association test for GWAS with multiple diseases

In a previous study, we proposed a new design and analysis strategy for Genome-wide Association Studies (GWAS) with multiple diseases but no controls. We have proposed to use an overall chi-square test to test for the association between an SNP with any one of the diseases. The overall chi-square test is not sensitive to the underlying model assumption; however, it does not use the information about the trend among the relative risks of the three genotypes. In this study, we propose a new overall test based on the chi-square partition method. The overall p-value of the proposed approach can be estimated by combining independent p-values from the more powerful one-sided tests which incorporate the trend among the relative risks. Simulation study and real data application show that the proposed test is more powerful and robust.

[1]  J. Li,et al.  Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix , 2005, Heredity.

[2]  V. Moskvina,et al.  On multiple‐testing correction in genome‐wide association studies , 2008, Genetic epidemiology.

[3]  D. Walkup,et al.  Association of Random Variables, with Applications , 1967 .

[4]  R. Fisher,et al.  Statistical Methods for Research Workers , 1930, Nature.

[5]  Eden R Martin,et al.  A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms , 2008, Genetic epidemiology.

[6]  Joseph L. Gastwirth,et al.  The Use of Maximin Efficiency Robust Tests in Combining Contingency Tables and Survival Analysis , 1985 .

[7]  Min-Jeong Kwak,et al.  A Robust Test for Two‐Stage Design in Genome‐Wide Association Studies , 2009, Biometrics.

[8]  Art B. Owen,et al.  Karl Pearson’s meta analysis revisited , 2009, 0911.3531.

[9]  J A Koziol,et al.  Comments on ‘Choosing an optimal method to combine P‐values’ by S. Won, N. Morris, Q. Liu, R. C. Elston, Statistics in Medicine 2009; 28:1537–1553 , 2009, Statistics in medicine.

[10]  Gang Zheng,et al.  Genetic model selection in two-phase analysis for case-control association studies. , 2008, Biostatistics.

[11]  Hon Keung Tony Ng,et al.  Testing for association in case-control genome-wide association studies with shared controls , 2016, Statistical methods in medical research.

[12]  Hon Keung Tony Ng,et al.  A Robust Method for Testing Association in Genome-Wide Association Studies , 2011, Human Heredity.

[13]  Min-Jeong Kwak,et al.  Improving Power for Testing Genetic Association in Case–Control Studies by Reducing the Alternative Space , 2010, Biometrics.

[14]  P. Armitage.  Tests for Linear Trends in Proportions and Frequencies , 1955 .

[15]  Joseph L. Gastwirth,et al.  Choice of scores in trend tests for case-control studies of candidate-gene associations , 2003 .

[16]  Xudong Huang,et al.  Age-adjusted nonparametric detection of differential DNA methylation with case–control designs , 2013, BMC Bioinformatics.

[17]  Joseph L. Gastwirth,et al.  Trend Tests for Case-Control Studies of Genetic Markers: Power, Sample Size and Robustness , 2002, Human Heredity.

[18]  Hon Keung Tony Ng,et al.  Design and analysis of multiple diseases genome-wide association studies without controls. , 2012, Gene.

[19]  Zhongxue Chen.  Association tests through combining p-values for case control genome-wide association studies , 2013 .

[20]  Kai Wang,et al.  Statistical tests of genetic association for case-control study designs. , 2012, Biostatistics.

[21]  Z Chen,et al.  Is the weighted z‐test the best method for combining probabilities from independent tests? , 2011, Journal of evolutionary biology.

[22]  A. Agresti,et al.  Categorical Data Analysis , 1991, International Encyclopedia of Statistical Science.

[23]  R. Elston,et al.  A powerful method of combining measures of association and Hardy–Weinberg disequilibrium for fine‐mapping in case‐control studies , 2006, Statistics in medicine.

[24]  Simon C. Potter,et al.  Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants , 2007, Nature Genetics.

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

[26]  Saralees Nadarajah,et al.  On the optimally weighted z-test for combining probabilities from independent studies , 2014, Comput. Stat. Data Anal..

[27]  Qingzhong Liu,et al.  A New Approach to Account for the Correlations among Single Nucleotide Polymorphisms in Genome-Wide Association Studies , 2011, Human Heredity.

[28]  Zhongxue Chen.  A new association test based on Chi‐square partition for case‐control GWA studies , 2011, Genetic epidemiology.

[29]  Qingzhong Liu,et al.  A new statistical approach to detecting differentially methylated loci for case control Illumina array methylation data , 2012, Bioinform..

[30]  Christophe G. Lambert,et al.  Learning from our GWAS mistakes: from experimental design to scientific method , 2012, Biostatistics.

[31]  J. Gastwirth.  ON ROBUST PROCEDURES , 1966 .

[32]  F. Dudbridge,et al.  Estimation of significance thresholds for genomewide association scans , 2008, Genetic epidemiology.

[33]  M J Podgor,et al.  Efficiency Robust Tests for Survival or Ordered Categorical Data , 1999, Biometrics.

[34]  Saralees Nadarajah,et al.  Detecting differentially methylated loci for Illumina Array methylation data based on human ovarian cancer data , 2013, BMC Medical Genomics.

[35]  Xavier Estivill,et al.  Maximizing association statistics over genetic models , 2008, Genetic epidemiology.

[36]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[37]  W. G. Cochran.  Some Methods for Strengthening the Common χ 2 Tests , 1954 .

[38]  R. Fisher.  Statistical methods for research workers , 1927, Protoplasma.

[39]  Jake K. Byrnes,et al.  Genome-wide association study of copy number variation in 16,000 cases of eight common diseases and 3,000 shared controls , 2010 .

[40]  M. Daly,et al.  Estimation of the multiple testing burden for genomewide association studies of nearly all common variants , 2008, Genetic epidemiology.