cogena_class: An S4 class to represent co-expressed gene-set enrichment...
In cogena: co-expressed gene-set enrichment analysis

An S4 class to represent co-expressed gene-set enrichment analysis result.

mat: 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.
clusterObjs: a list contains clustering results.
Distmat: the distance matrix.
measures: a list of the enrichment results.
upDn: the enrichment score for up or down-regulated genes.
clMethods: clustering method.
labels: the label of genes
nClust: 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.
metric: 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.
method: For hierarchical clustering (hclust and agnes), the agglomeration method used. The default is "complete". Available choices are "ward", "single", "complete", and "average".
annotation: logical matrix of biological annotation with row be DE gene column be gene sets and value be logical.
sampleLabel: character vector with names are sample names. Only used for plotting.
ncore: the number of cores used.
gmt: the gmt file used
call: the called function