RVtests (version 1.0)

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, if missing, equal to npermutation.

min.nonsignificant.counts

Minimum nonsignificant counts, if missing, equal to 10.

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

C. Xu, M. Ladouceur, Z. Dastani, J. B. Richards, A. Ciampi, C. M.T. Greenwood (2012), Multiple regression methods show great potential for rare variant association tests, PLoSONE.

See Also

PLS, RR