Is the overlap between two gene expression samples significant? I have performed an experiment to study the response of a yeast (that contains 5000 genes) to stress caused by heat shock. I have one list of 48 genes that are overexpressed at 37ºC and another list of 145 genes that are overexpressed at 42ºC. There are 38 genes that are overexpressed in both of them.
By chance I expected only 1 gene overexpressed in both of them, how can I calculate if the overlap that I have obtained is significantly? How can I obtained the $p$ value? I know nothing about biostatistic or math software. Thanks you very much!!! Any help will be very welcome :) 
 A: The table looks like this
                37 deg C
42 deg C     yes      no
yes          38       97
no           10      4855

yes and no refer to cases overexpressed or not
I ran Fisher's exact test in SAS
The output is pasted below:
Laura Gene expression data 


The FREQ Procedure


Statistics for Table of Group by expressed

Fisher's Exact Test 
Cell (1,1) Frequency (F) 4855 
Left-sided Pr <= F 1.0000 
Right-sided Pr >= F 4.776E-53 

Table Probability (P) 8.132E-51 
Two-sided Pr <= P 4.776E-53 
Sample Size = 5000

You see here that the p value for Fisher's Exact test is very small far less than 0.0001.
This shows exactly what you stated the observed 38 overexpressed at both temperatures is far greater than what you wou expect under independence which as you stated would be 1.296.
A: The exact test referred to by Michael is probably the way I would recommend using to solve the problem (fewest assumptions).  For reference, the corresponding common statistical test would be a $\chi^2$ test of independence.
