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GWAX

GWAX.Rmd

Overview

GWAX is short for genome-wide association study by proxy, which is an approach used to identify genomic variants that are statistically associated with a risk for a disease, exactly as GWAS. The key difference is the regressand which GWAS uses to do simple linear regression on. GWAX makes a proxy case-control status based on the individual’s family history. So if the individual’s case-control status is zero, meaning not having the disease, but just one the individual’s parents case-control status is one, meaning having the disease, the individual gets a proxy status of one. In other words any GWAX therefore accounts for some family history and heritability, which should give more useful information to the analysis.

Example Run on 100,000x100,000 Dataset

Using GWAX on the same simulated data that we analyzed in the GWAS article we get the following results

We see that GWAX performs slightly better than GWAS with 177 true positives compared to 164 for GWAS. See a full comparison between all the methods in the LTFH article vignette("LTFH"). We refer the reader to the original paper on GWAX by Liu, J.Z. et al. (2017) for more information about the method.

References