RVtests (version 1.2)

PCR: Principal Components Regression for RV 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

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