genecl-class


An S4 class to represent co-expressed gene


cogena is a workflow for co-expressed gene-set enrichment analysis.
It aims to discovery smaller scale, but highly correlated cellular events that
may be of great biological relevance. A novel pipeline for drug discovery and
drug repositioning based on the cogena workflow is proposed. Particularly,
candidate drugs can be predicted based on the gene expression of disease-related
data, or other similar drugs can be identified based on the gene expression
of drug-related data. Moreover, the drug mode of action can be disclosed by
the associated pathway analysis. In summary, cogena is a flexible workflow for
various gene set enrichment analysis for co-expressed genes, with a focus on
pathway/GO analysis and drug repositioning.

Zhilong Jia

cogena

co-expressed gene-set enrichment analysis

genecl-class function

 <dl>
<dt><code>mat</code></dt><dd>Differentially expressed gene expression profilings. Either a 
numeric matrix, a data.frame, or an ExpressionSet object. Data frames must
contain all numeric columns. In all cases, the rows are the items to be 
clustered (e.g., genes), and the columns are the samples.</dd> <dt><code>clusterObjs</code></dt><dd>a list contains clustering results.</dd> <dt><code>Distmat</code></dt><dd>the distance matrix.</dd> <dt><code>clMethods</code></dt><dd>clustering method.</dd> <dt><code>labels</code></dt><dd>the label of genes</dd> <dt><code>nClust</code></dt><dd>A numeric vector giving the numbers of clusters to be 
evaluated. e.g., 2:6 would evaluate the number of clusters ranging from 
2 to 6.</dd> <dt><code>metric</code></dt><dd>the distance measure to be used. It must be one of 
"euclidean","maximum", "manhattan", "canberra", "binary", 
"pearson", "abspearson", "correlation", "abscorrelation", 
"spearman" or "kendall". Any unambiguous substring can be 
given. In detail, please reference the parameter method in 
amap::Dist. Some of the cluster methods could use only part 
of the metric. Please reference the manual of cogena.</dd> <dt><code>method</code></dt><dd>For hierarchical clustering (hclust and agnes), the 
agglomeration method used. The default is "complete". Available 
choices are "ward", "single", "complete", and "average".</dd> <dt><code>ncore</code></dt><dd>the number of cores used.</dd> <dt><code>call</code></dt><dd>the called function</dd> </dl>

genecl-class: An S4 class to represent co-expressed gene

Description

Arguments

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