Description Usage Arguments Value Author(s) References Examples
A variance-component based testing procedure to test for the total effect of methylation loci and mRNA expression across a network after specifying an underlying disease risk model which applies to all genes in the gene set of interest.
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iCPG |
A list of J CpG matrices with dimensions nxp_{j}. |
iGE |
An nxJ matrix of gene expression values. |
iY |
An nx1 dichotomous outcome vector. |
iX |
An nxr covariate matrix. |
imodel |
The specified disease risk model for the whole gene set: 'mgc', 'mg', or 'm'. |
iapprox |
The preferred method of gene-set p-value calculation: 'pert' or 'davies' |
i.omniseed |
A Jx1 seed vector. |
no.pert |
If using 'pert', the no. perturbations per gene level test; defaults to 1000. |
gsp.emp |
If using 'pert': The method of calculating the perturbation based p-value: empirical (TRUE) or parametric (FALSE). |
A list with the following components:
p |
The p-value for the joint, integrative total effect test for the gene set under a pre-specified disease risk model for the whole gene set. |
iapprox |
The method of gene-set p-value calculation: 'pert' or 'davies'. |
imodel |
The user-specified disease risk model for the whole gene set. |
p.emp |
If using 'pert', and if gsp.emp is set to 'FALSE', returns the empirical p-value in addition to the approximated p-value. |
gsp.emp |
A logical value to indicate the method of calculation for the perturbation based p-value: TRUE for empirical, FALSE for parametric. |
Su H. Chu & Yen-Tsung Huang
Chu S.H. and Huang Y-T. (2017) Integrative genomic analysis of biological gene sets with applications in lung cancer. (Revise and Resubmit)
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