Description Usage Arguments Details Value Author(s) References See Also
Use SPLS for selecting significant variants and testing the variants associated with disease traits.
1 2 |
x |
Genotype matrix, each row as an individual and each column as a snp |
y |
Phenotype vector |
scale |
see spls |
ncomp |
Number of components |
eta.grid |
see spls |
size.max |
Maximum number of variants included |
a |
Penalty parameter for information criterion, a=2 for AIC. |
npermutation |
Number of permutation, if less than 1, the permutation will not be run. |
npermutation.max |
Maximum permutation |
min.nonsignificant.counts |
Minimum nonsignificant counts |
Use spls package to implement SPLS and an information criterion (AIC, BIC, GIC) to select a set of variants.
nonsignificant.counts |
Counts of permuted data that have a higher score than unpermuted data. |
pvalue.empirical |
Empirical pvalue via permutation |
pvalue.nominal |
Not availabe |
vs |
The selected variants |
total.permutation |
Total permutation |
C. Xu
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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.