GeneInfo

<p>The data set contains the entrezIdentifiers, symbols and names
of the used genes in the CMAP MCF7 data.</p>

datasets

Several integrative data methods in which information of objects from different data sources can be combined are included in the IntClust package. As a single data source is limited in its point of view, this provides more insight and the opportunity to investigate how the variables are interconnected. Clustering techniques are to be applied to the combined information. For now, only agglomerative hierarchical clustering is implemented. Further, differential gene expression and pathway analysis can be conducted on the clusters. Plotting functions are available to visualize and compare results of the different methods.

Marijke Van Moerbeke

IntClust

Integrated Data Analysis via Clustering

GeneInfo function

<p>The format is:
 'data.frame':	2434 obs. of  3 variables:
 $ ENTREZID: Factor w/ 2434 levels "10001","100129361",..: 1 2 3 4 5 6 7 8 9 10 ...
  ..- attr(*, "names")= chr  "1" "2" "3" "4" ...
 $ SYMBOL  : Factor w/ 2434 levels "AARS","ABCA1",..: 1213 1132 1486 2178 1914 1133 2175 891 2003 1134 ...
  ..- attr(*, "names")= chr  "1" "2" "3" "4" ...
 $ GENENAME: Factor w/ 2434 levels "1-acylglycerol-3-phosphate O-acyltransferase 5 (lysophosphatidic acid acyltransferase, epsilon)",..: 1199 925 1586 2153 1895 2374 2067 908 1983 926 ...
  ..- attr(*, "names")= chr  "1" "2" "3" "4" ...</p>

GeneInfo: The gene info data frame

Description

Usage

Arguments

Format