getExpp

`getExpp` perform t-test on Expression profile data

Identify Cancer Dysfunctional Sub-pathway by integrating gene expression, DNA methylation and copy number variation, and pathway topological information. 1)We firstly calculate the gene risk scores by integrating three kinds of data: DNA methylation, copy number variation, and gene expression.  2)Secondly, we perform a greedy search algorithm to identify the key dysfunctional sub-pathways within the pathways for which the discriminative scores were locally maximal. 3)Finally, the permutation test was used to calculate statistical significance level for these key dysfunctional sub-pathways.

Junwei Han

ICDS

Identification of Cancer Dysfunctional Subpathway with Omics
Data

Baotong Zheng

Siyao Liu

getExpp function

<dl><dt>exp_data</dt>
<dd>A data frame, the expression profile to calculate p-value for each gene, the rownames should be the symbol of genes.</dd>
<dt>label</dt>
<dd>A vector of 0/1s, indicating the class of samples in the expression profile, 0 represents case, 1 represents control.</dd>
<dt>p.adjust</dt>
<dd>Logical,tell if returns corrected p-values</dd>
<dt>method</dt>
<dd>Correction method,which can be one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY",</dd></dl>

Arguments

getExpp — getExpp

<dl>

<dt>exp_data</dt>
<dd>A data frame, the expression profile to calculate p-value for each gene, the rownames should be the symbol of genes.</dd>


<dt>label</dt>
<dd>A vector of 0/1s, indicating the class of samples in the expression profile, 0 represents case, 1 represents control.</dd>


<dt>p.adjust</dt>
<dd>Logical,tell if returns corrected p-values</dd>


<dt>method</dt>
<dd>Correction method,which can be one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY",</dd>

</dl>

getExpp: getExpp

Description

Usage

Value

Arguments

Details

Examples