Epistasis network identified
by the W-test: Red line indicate significant interactions found in WTCCC
bipolar data set, and Blue line indicates significant interactions found in
the American GAIN bipolar data set. The purple circle is the gene that is
replicated in the two independent data sets.
R package: wtest in CRAN
We introduce a W-test to
measure the distribution differences between the case and control groups.
The measure is model-free and is constructed through contingency tables
created by one or more variables. The statistic follows a chi-squared
distribution with data-set adaptive degrees of freedom, estimated from
small bootstrapped samples from the data under the null hypothesis. The
advantage of the test is as follows:
(1) it inherits a probability distribution
thus p-value can be efficiently calculated; the method is scalable to
(2) it makes use of bootstrapped sample to
estimate an data-corrected degrees of freedom, and offers an more accurate
probability distribution under complicated data structures, such as low
frequency minor allele variables or mild population stratification. It is
robust when sample size decreases.
(3) the test statistics is
constructed from an integrated odds ratio, and takes a retrospective
design, there is suitable to apply on case-control data set.
Ref: Wang, Sun et
al. 2016 Nucleic Acids Research (pdf)
W-test collapsing for rare variants association test:
This work extends the
W-test as a rare variant association tool through collapsing single
marker’s contingency tables within a genomic region, thus it belongs to the
burden test category. The test has good power for rare variants and is very
efficient. (Sun, Weng et
al 2016 Genetic Epidemiology)
W-pure for detecting pure SNP-SNP interactions: work in