Figure 6

Overlap of differentially expressed genes identified by three analyses: ANOVA-p149 = 149 genes derived from the ANOVA analysis of all data, LD-p54 = linear discriminant list of 54 genes from all data, and ANOVA-i12 = twelve genes resulting from a comparison of differentially expressed genes from the ANOVA analysis of individual tumors compared to parental cell lines. An estimate for the statistical significance for the overlap of differentially expressed genes by the 3 analytical methods was estimated by calculating the product of individual probabilities for the results of each analytical method applied to 3531 genes. The null hypothesis in this case is that each method's "call" as to a given gene's differential expression is independent of the call made by the other two methods. Thus if p1, p2, and p3 represent the chance that each method calls a given gene as differentially expressed (easily estimated as number of genes called/ number of total genes), the chance that all three methods do so is simply pAll = p1*p2*p3 = (54/3531)*(149/3531)*(12/3531) = 2.193e-5. Under our null hypothesis, the total number of genes called by all three methods k will follow a binomial distribution with parameters p = pAll, n = 3531 where P(k = L) ~ Bin(pAll, N). Standard calculation techniques allow us to calculate a p-value for this; i.e. p = P(k > = K) – the chance under the null hypothesis we see as much or more overlap than was actually observed. For our data, we thus have p = P(k> = 7) < 1E-6. Thus, if the methods identified random noise as differential expression, they would be very unlikely to produce the overlap observed, thus supporting the statistical significance of the results. The heat maps indicate relative fold-induction or suppression in a linear color-encoded scale shown at the bottom. Mean ratios are indicated by X, C = colon, B = breast, L = lung, P = prostate, O = ovary.