Dear All, I have a dataframe of 1000 rows and 4 columns. Each row represents a pair of vectors (in my case a pair of genes) while the columns represent the following estimate.A: spearman correlation coefficient of gene[i] and gene[j] expression across 120 samples from cancer type A prob.A: Probability value associated with the estimate.A as inferred from cor.test estimate.B: spearman correlation coefficient of gene[i] and gene[j] expression across 48 samples from cancer type B prob.B: Probability value associated with the estimate.A as inferred from cor.test To sum up the data.frame will look like S<-data.frame(estimate.A=runif(1000,-1,1),prob.A=runif(1000,0,1),estimate.B=runif(1000,-1,1),prob.B=runif(1000,0,1)) I want to calculate the conditional probability for all the pair of genes showing negative correlation in B (at p.value < 0.01) when they show a strong negative correlation in A (again at p.value < 0.01). I was thinking in the lines of using the "prob" package to estimate the conditional probability but I am not able to figure out the correct way to do so in my case. Thanks for any help in advance. -- Swaraj Basu Institute of Biomedicine University of Gothenburg [[alternative HTML version deleted]]