text: user1226: I'm looking at some microarray data. For the first time I've calculated a moderated T statistic from limma.
  Is there any standard practice for where to cut off that value? For log2 fold change I usually cut off at +/- 1.5 and adjust accordingly; for adjusted p value I cut off at p<0.01 and adjust accordingly. 
  These moderated T statistics seem a little higher than log2 fold change and I'm not sure what is generally accepted as significant.
  Thanks!
  
  user77: You're misinterpreting the moderated T-statistic, it's basically the fold-change divided by its variance. The p-value comes directly from that, so if you filter by moderated fold-change you're just setting an unknown (unless you go through the trouble of figuring it out) p-value threshold. Instead, do exactly as you've been doing and set appropriate (adjusted) p-value and fold-change thresholds.
  
original_text: 1226: <p>I'm looking at some microarray data. For the first time I've calculated a <a href="https://support.bioconductor.org/p/6124/" rel="nofollow noreferrer">moderated T statistic</a> from <a href="http://bioconductor.org/packages/release/bioc/html/limma.html" rel="nofollow noreferrer">limma</a>.</p>
  
  <p>Is there any standard practice for where to cut off that value? For log2 fold change I usually cut off at +/- 1.5 and adjust accordingly; for adjusted p value I cut off at p&lt;0.01 and adjust accordingly. </p>
  
  <p>These moderated T statistics seem a little higher than log2 fold change and I'm not sure what is generally accepted as significant.</p>
  
  <p>Thanks!</p>
   77: <p>You're misinterpreting the moderated T-statistic, it's basically the fold-change divided by its variance. The p-value comes directly from that, so if you filter by moderated fold-change you're just setting an unknown (unless you go through the trouble of figuring it out) p-value threshold. Instead, do exactly as you've been doing and set appropriate (adjusted) p-value and fold-change thresholds.</p>
  