An Investigation of the Properties of Gene-Based Tests of GWAS Data: Simulations and Analyses of ADHD GWAS Data Open Access

Weinstock, Joshua (2015)

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Genome-wide association studies (GWAS) have become a useful tool in recent years for elucidating the etiology of a variety of complex traits. Although these studies have shown promising findings in the field of psychiatric genetics, conventional single-SNP testing methods pose a number of challenges of both a statistical and biological nature. These challenges make alternative association testing methods, such as gene-based tests, attractive. In the current study, I used simulations and analyses of real data to evaluate the properties of several of the aforementioned gene-based tests, as well as to attempt to answer some questions raised by the application of several gene-based tests to real ADHD GWAS data from four samples. The issues addressed by the simulations included an examination of their Type I Error rates and statistical power across several plausible scenarios, as well as the impact of differing LD among the SNPs on the gene-based tests that use summary data and differences in test performance with genes of differing length, number of LD blocks, and number of causal variants per block. Analyses of the real ADHD GWAS data were used to evaluate differences among the gene-based tests in finding associated genes.

Table of Contents

Introduction 3

Discussion of GWAS 3

Gene-based tests 4

The current study 8

Methods 8

Simulation 9

PGC Data 12

Meta analysis 14

Results 14

Type-1 simulations 14

GERM sample 16

CHOP sample 20

IMAGE1 sample 23

PUWM sample 27

Meta-analysis 30

Power simulations 31

Discussion 36

Limitations 39

Future directions 40

Conclusion 40

Works cited 42

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