Clustering data with heatmap algorithm for (Study ST004207)

This analysis uses the 'heatmap.2' function of gplots package in the R statistics environment


The rows are scaled to have mean=0 and standard deviation=1

Factors:

F1Factor:in vivo | Sample source:human ccRCC
F2Factor:in vivo | Sample source:human kidney
F3Factor:in vivo | Sample source:mouse ccRCC
F4Factor:in vivo | Sample source:mouse kidney
F5Factor:WIT 10mins | Sample source:human ccRCC
F6Factor:WIT 10mins | Sample source:human kidney
F7Factor:WIT 15mins | Sample source:human ccRCC
F8Factor:WIT 15mins | Sample source:human kidney
F9Factor:WIT 30mins | Sample source:mouse ccRCC
F10Factor:WIT 30mins | Sample source:mouse kidney
F11Factor:WIT 45mins | Sample source:human ccRCC
F12Factor:WIT 45mins | Sample source:human kidney
F13Factor:WIT 5mins | Sample source:mouse ccRCC
F14Factor:WIT 5mins | Sample source:mouse kidney
F15Factor:WIT 60mins | Sample source:human ccRCC
F16Factor:WIT 60mins | Sample source:human kidney
F17Factor:WIT 60mins | Sample source:mouse ccRCC
F18Factor:WIT 60mins | Sample source:mouse kidney
Data matrix
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