text: user1377: Using edgeR for differential analysis between Tumor and Normal gave me differential expressed genes with logFC, logCPM, PValue and FDR. 
  From the details of glmTreat function I see that logCPM is average log2-counts per million, the average taken over all libraries.
  The output table I got from glmTreat:
  Geneid     logFC  unshrunk.logFC    logCPM  PValue       FDR
  Gene1   4.985298235 5.573931983 1.236660486 1.55E-54    1.87E-50
  Gene2   4.613438634 5.52126484  0.920343233 2.59E-53    1.56E-49
  Gene3   5.250601296 5.356432653 2.751294034 2.48E-50    9.95E-47
  Gene4   4.943049159 5.379741165 1.361393757 2.06E-45    6.19E-42
  Gene5   6.100121754 6.117580436 5.774385315 2.95E-43    7.11E-40
  Gene6   4.722697891 5.320461275 1.120685402 3.05E-42    6.11E-39
  Gene7   5.246129853 5.497012001 1.902992053 2.78E-40    4.78E-37
  Gene8   3.878773277 4.956636276 0.776208741 8.66E-39    1.30E-35
  Gene9   4.441752496 4.94930499  1.132652682 4.37E-38    5.83E-35
  
  To calculate logCPM given in the above table manually I did like this:
  logCPM <- cpm(y, prior.count=2,  log=TRUE)
  
  I got the logCPM values for all the genes. Then I calculated Average across all the samples for each gene. I got like below:
  Geneid  Average
  Gene1   0.686560246
  Gene2   0.617115826
  Gene3   1.075975225
  Gene4   0.692050878
  Gene5   1.277556065
  Gene6   0.638358189
  Gene7   0.689323163
  Gene8   0.60700396
  Gene9   0.662115092
  
  Why there is so difference? Where I'm doing wrong?
  
  user77: If you want the values by group then subset y to contain the samples of interest and then feed that to aveLogCPM().
  
original_text: 1377: <p>Using edgeR for differential analysis between Tumor and Normal gave me differential expressed genes with logFC, logCPM, PValue and FDR. </p>
  
  <p>From the details of glmTreat function I see that logCPM is average log2-counts per million, the average taken over all libraries.</p>
  
  <p>The output table I got from glmTreat:</p>
  
  <pre><code>Geneid     logFC  unshrunk.logFC    logCPM  PValue       FDR
  Gene1   4.985298235 5.573931983 1.236660486 1.55E-54    1.87E-50
  Gene2   4.613438634 5.52126484  0.920343233 2.59E-53    1.56E-49
  Gene3   5.250601296 5.356432653 2.751294034 2.48E-50    9.95E-47
  Gene4   4.943049159 5.379741165 1.361393757 2.06E-45    6.19E-42
  Gene5   6.100121754 6.117580436 5.774385315 2.95E-43    7.11E-40
  Gene6   4.722697891 5.320461275 1.120685402 3.05E-42    6.11E-39
  Gene7   5.246129853 5.497012001 1.902992053 2.78E-40    4.78E-37
  Gene8   3.878773277 4.956636276 0.776208741 8.66E-39    1.30E-35
  Gene9   4.441752496 4.94930499  1.132652682 4.37E-38    5.83E-35
  </code></pre>
  
  <p>To calculate logCPM given in the above table manually I did like this:</p>
  
  <pre><code>logCPM &lt;- cpm(y, prior.count=2,  log=TRUE)
  </code></pre>
  
  <p>I got the logCPM values for all the genes. Then I calculated Average across all the samples for each gene. I got like below:</p>
  
  <pre><code>Geneid  Average
  Gene1   0.686560246
  Gene2   0.617115826
  Gene3   1.075975225
  Gene4   0.692050878
  Gene5   1.277556065
  Gene6   0.638358189
  Gene7   0.689323163
  Gene8   0.60700396
  Gene9   0.662115092
  </code></pre>
  
  <p>Why there is so difference? Where I'm doing wrong?</p>
   77: <p>If you want the values by group then subset <code>y</code> to contain the samples of interest and then feed that to <code>aveLogCPM()</code>.</p>
  