Input data:
	TFBSs intersected with genes in .bed
	For each tissue:
		Genes with Differential Expression

Desired Output:
	TFs differentially expressed in certain tissues

Using pandas dataframe to load the .bed file
Using a dict to load the gene list of each tissue

Create a dataframe with the number of BSs of a TF in each tissue
	Store mean number of BSs per tissue of each TF
#The "diffFactor" measures how much the number of BSs of a TF in a tissue is above the mean.
Calculate diffFactor for each pair of tissue and TF, store it all in a pandas dataframe.
Filter the top 5% values.
Sort by diffFactor.
Save results.

New measure to representation:
            WithBSToTF ALL
TESTIS      127         1225
ALL-TISSUE  472         21000


Random simulation:
Select random sets of 1225 genes
    Count number of genes with BS to TF
Make a distribuition
Position the amount found (127) in the distribution

Usar Z score?
Usar x²