Perform sequential tests of pleiotropy to determine the number of traits, and which traits, are associatd with a vector of genotypes. For gaussian traits without covariates.
pleio.q.sequential(obj.fit, pval.threshold)
A list containing:
p-value of the final test from the sequential testing
index of columns of y that have non-zero betas. These indices indicate which traits are associated with the genotype, accounting for the correlations among the traits.
result of pleio.q.fit
p-value for rejecting the null hypothesis of the specified number of non-zero betas.
Dan Schaid and Jason Sinnwell
Perform sequential tests of pleiotropy, starting at the usual multivarite null hypothesis that all coefficients = 0. If this test rejects because the p-value < pval.threshold, then allow one coefficient to be non-zero in order to test whether the remaining coefficients = 0. If the test of one non-zero coefficient rejects, then allow two non-zero coefficients, considering all possible combinations of two non-zero coefficients and test whether the remaining coefficients = 0. Continue this sequential testing until the p-value for a test is greater than the specific pval.threshold. The step at which the p-value > pval.threshold determines which traits are associated with the genotype. If there are m traits, the sequential testing stops either when p-value > pval.threshold, or when (m-1) traits are tested. If the p-value remains less than pval.threshold when testing (m-1) traits, this implies that all m traits are associated with the genotype.
Schaid DJ, Tong X, Larrabee B, Kennedy RB, Poland GA, Sinnwell JP. Statistical Methods for Testing Genetic Pleiotropy. To appear in Genetics, 2016.
data(pleio.qdemo)
fit <- pleio.q.fit(y, geno)
test.seq <- pleio.q.sequential(fit, pval.threshold=.05)
test.seq
Run the code above in your browser using DataLab