sampleLabel

Generate data structure of sample labels

It aims to find significant pathways through
network topology information. It has several advantages compared
with current pathway enrichment tools. First, pathway node instead
of single gene is taken as the basic unit when analysing networks
to meet the fact that genes must be constructed into complexes to
hold normal functions. Second, multiple network centrality measures are
applied simultaneously to measure importance of nodes from different
aspects to make a full view on the biological system. CePa extends
standard pathway enrichment methods, which include both over-representation
analysis procedure and gene-set analysis procedure.
<doi:10.1093/bioinformatics/btt008>.

Zuguang Gu

CePa

Centrality-Based Pathway Enrichment

sampleLabel function

<dl>
 <dt>label</dt>
<dd>sample label vector</dd> <dt>treatment</dt>
<dd>treatment label</dd> <dt>control</dt>
<dd>control label</dd>
</dl>

Arguments

Author

Generate data structure of sample labels — sampleLabel

<dl>


 <dt>label</dt>
<dd>sample label vector</dd>

 <dt>treatment</dt>
<dd>treatment label</dd>

 <dt>control</dt>
<dd>control label</dd>


</dl>

sampleLabel: Generate data structure of sample labels

Description

Usage

Value

Arguments

Author

Details

Examples