Skip to main content
Figure 1 | BMC Bioinformatics

Figure 1

From: Iterative Group Analysis (iGA): A simple tool to enhance sensitivity and facilitate interpretation of microarray experiments

Figure 1

Principle of Iterative Group Analysis. The left panels shows a notional microarray result for 14 genes (n = 14), which are sorted by decreasing fold-change. 5 of the genes (filled circles) belong to the functional class of interest (x = 5). For each class member the p-value was calculated according to the hypergeometric equation given in the text, using the t- and z-values shown next to each gene. The left panel shows those p-values plotted against the position of the class member. The minimum is found at position 3 and is used to determine the cutoff for this group, i.e. group members 1 to 3 would be listed as "most likely to be up-regulated". The corresponding p-value (0.1) would be assigned as the PC-value for this group.

Back to article page