title: Bonferroni correction of p-values from hypergeometric analysis
body: <p>I have performed a hypergeometric analysis (using a python script) to investigate enrichment of GO-terms in a subset of genes. An example of my output is as follows:</p>
  
  <pre><code>GO00001 1500    300 200 150 5.39198144708e-77
  GO00002 1500    500 400 350 1.18917839281e-160
  GO00003 1500    400 350 320 9.48402847878e-209
  GO00004 1500    100 100 75  3.82935778527e-82
  GO00005 1500    100 80  80  2.67977253966e-114
  </code></pre>
  
  <p>where</p>
  
  <pre><code>Column1 = GO ID
  Column2 = Total sum of all terms in the original dataset
  Column3 = Total sum of [Column 1] IDs in the original dataset
  Column4 = Sum of all terms in the subset
  Column5 = Sum of [Column 1] IDs in subset
  Column6 = pvalue derived from hypergeometric test
  </code></pre>
  
  <p>I know that I must multiply the number of experiments by the pvalue but I'm not sure how to do this with the data I have. Am I calculating from the subset or a combination of the original dataset and the subset? For example, would it be:</p>
  
  <pre><code>Column2 * Column5 * pvalue
  Column3 * Column5 * pvalue
  Column4 * Column5 * pvalue
  </code></pre>
  
  <p>I apologise if this seems like a stupid question but I just can't seem to get my head around it. Many thanks in advance!</p>