text: user1377: I have the raw counts for RNA-Seq data. I converted counts data to logCPM using edgeR package.
  Lets say I have a dataframe A with 15000 genes as rows and 100 samples as columns with counts data. I have used following code from edgeR tutorial.
  logCPM <- cpm(A, prior.count=2, log=TRUE)
  head(logCPM)[1:5,1:5]
                 Sample1          Sample2          Sample3         Sample4
  A1BG          -1.019429        0.8333739        -1.192960       -0.6717287
  A2M            7.622280        7.8057767         7.932570        8.6409077
  A2ML1          1.004541        1.0909119         5.462613        6.4149348
  A4GALT         2.126502        1.8403954         5.322601        2.9469345
  AAAS           5.785888        5.1639501         5.259789        5.3248026
                 Sample5
  A1BG          0.3121975
  A2M           9.1949911
  A2ML1         9.4740594
  A4GALT        2.9214979
  AAAS          4.3708063
  
  After converting counts to logCPM I see there is another command for scaling which is used for heatmaps.
  logCPM <- t(scale(t(logCPM)))
  
  It is given there that scaling each row (each gene) to have mean zero and standard deviation one in page 15 edgeR
  Is this nothing but z-score? or Is there any otherway to calculate z-score from logCPM data?
  thanq
  
  user939: Yes this is nothing but a z-score. The scale function calculates column z-scores, but since you use t (transpose), it is actually performed on rows. There are many other ways to calculate z-scores, but if done correctly they will all give the same results.
  
original_text: 1377: <p>I have the raw counts for RNA-Seq data. I converted counts data to logCPM using edgeR package.</p>
  
  <p>Lets say I have a dataframe <code>A</code> with 15000 genes as rows and 100 samples as columns with counts data. I have used following code from edgeR tutorial.</p>
  
  <pre><code>logCPM &lt;- cpm(A, prior.count=2, log=TRUE)
  head(logCPM)[1:5,1:5]
                 Sample1          Sample2          Sample3         Sample4
  A1BG          -1.019429        0.8333739        -1.192960       -0.6717287
  A2M            7.622280        7.8057767         7.932570        8.6409077
  A2ML1          1.004541        1.0909119         5.462613        6.4149348
  A4GALT         2.126502        1.8403954         5.322601        2.9469345
  AAAS           5.785888        5.1639501         5.259789        5.3248026
                 Sample5
  A1BG          0.3121975
  A2M           9.1949911
  A2ML1         9.4740594
  A4GALT        2.9214979
  AAAS          4.3708063
  </code></pre>
  
  <p>After converting counts to <code>logCPM</code> I see there is another command for scaling which is used for heatmaps.</p>
  
  <pre><code>logCPM &lt;- t(scale(t(logCPM)))
  </code></pre>
  
  <p>It is given there that <code>scaling each row (each gene) to have mean zero and standard deviation one</code> in page 15 <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934518/pdf/f1000research-5-9996.pdf" rel="nofollow noreferrer">edgeR</a></p>
  
  <p>Is this nothing but z-score? or Is there any otherway to calculate z-score from logCPM data?</p>
  
  <p>thanq</p>
   939: <p>Yes this is nothing but a z-score. The scale function calculates column z-scores, but since you use t (transpose), it is actually performed on rows. There are many other ways to calculate z-scores, but if done correctly they will all give the same results.</p>
  