PCR: Principal Components Regression for RV tests

In RVtests: Rare Variant Tests

Description

Use principal components for testing rare variants association with disease traits.

Usage

PCR(x, y, scale = FALSE, ncomp, varpercent, 
	npermutation = 100, npermutation.max, min.nonsignificant.counts)

Arguments

x	Genotype matrix
y	Phenotype vector
scale	If TRUE, scale x and y.
ncomp	Number of components, which could be a vector containing a set of numbers.
varpercent	Explained variance percentage
npermutation	Number of permutation, if less than 1, the permutation will not be run.
npermutation.max	Maximum permutation
min.nonsignificant.counts	Minimum nonsignificant counts

Value

score	Correlation between y and y_est
nonsignificant.counts	Counts of permuted data that have a higher score than unpermuted data.
pvalue.empirical	Empirical pvalue via permutation
pvalue.nominal	Theoretical pvalue, not available now.
total.permutation	Total permutation
ncomp.varp	Number of components required for specified variance percentage

Author(s)

C. Xu

References

Xu C, Ladouceur M, Dastani Z, Richards JB, Ciampi A, Greenwood CMT. (2012) Multiple Regression Methods Show Great Potential for Rare Variant Association Tests. PLoS ONE 7(8): e41694. doi:10.1371/journal.pone.0041694

See Also

PLS, RR

RVtests documentation built on May 1, 2019, 9:51 p.m.