<p>Try to use <code>DElist()</code> function before you transform, and also make rownames first.</p>

<pre><code>counts &lt;- prac_count_10[,-1]

rownames(counts) &lt;- prac_count_10[,1]

DGE1 &lt;- DGEList(counts)
</code></pre>

<p>And then continue with your voom...</p>

CC BY-SA 4.0
2019-04-09T08:21:50.847Z
Thank you. what package is DElist in?
holly
CC BY-SA 4.0
2019-04-09T08:23:40.500Z
That would be edgeR.
benn
CC BY-SA 4.0
2019-04-09T08:31:09.270Z
If I do:   ``````prac_count <- data.frame(prac_count, row.names=1), counts<- prac_count[,1], rownames(counts) <- prac_count[,1], DGE1 <-DGEList(counts) `````` If doesn't work... have I missed a step? Thank you so much
holly
CC BY-SA 4.0
2019-04-09T08:48:04.480Z
That's not the code I gave in my answer, is it?
benn
CC BY-SA 4.0
2019-04-09T15:47:51.217Z
Don't mention it! Good luck with it.
benn
CC BY-SA 4.0
2019-04-09T07:31:36.970Z
2019-04-09T07:31:36.970Z
benn
<p>I have RNA seq data of raw gene counts that I want to transform for linear modelling. I am trying to voom transform, to do a weighted analysis.</p>

<p>Data frame: prac_count_10</p>

<pre><code>gene         S1     S2    S3   S4    S5 
ENG0000456   0      1     10   145   24
ENG0000458   7      2     9    0     0
ENG0000657   76     12    56   10    2 
ENG0000689   0      0     0    3     5

</code></pre>

<p>Code:</p>

<pre><code>prac_prac_10 &lt;- voom(prac_count_10[,2:5], design=NULL, lib.size=NULL, 
  normalize.method = "none", span = 0.5

</code></pre>

<p>However this doesn't give an output with the gene sample names and logCPM values. Would like an output with gene id's and logCPM values for linear modelling.</p>

<p>Also tried:</p>

<pre><code>cpm &lt;- cpm(prac_count_10)
lcpm &lt;- cpm(prac_count_10, log=TRUE)


<span class="math-container">````````````</span>
</code></pre>

<r><limma>
Voom transformation of RNA seq raw counts data
# Voom transformation of RNA seq raw counts data

(Asked by: username_0 on 2019-04-08)

I have RNA seq data of raw gene counts that I want to transform for linear modelling. I am trying to voom transform, to do a weighted analysis.
Data frame: prac_count_10
gene         S1     S2    S3   S4    S5 
ENG0000456   0      1     10   145   24
ENG0000458   7      2     9    0     0
ENG0000657   76     12    56   10    2 
ENG0000689   0      0     0    3     5


Code:
prac_prac_10 <- voom(prac_count_10[,2:5], design=NULL, lib.size=NULL, 
  normalize.method = "none", span = 0.5


However this doesn't give an output with the gene sample names and logCPM values. Would like an output with gene id's and logCPM values for linear modelling.
Also tried:
cpm <- cpm(prac_count_10)
lcpm <- cpm(prac_count_10, log=TRUE)


````````````

**Tags:** r, limma

---

## 1 answers

### Answer by username_1 on 2019-04-09. Score: 1 | Accepted answer

Try to use DElist() function before you transform, and also make rownames first.
counts <- prac_count_10[,-1]

rownames(counts) <- prac_count_10[,1]

DGE1 <- DGEList(counts)

And then continue with your voom...

> **Comments:**
> **username_0**: Thank you. what package is DElist in?  
> **username_1**: That would be edgeR.  
> **username_0**: If I do:   ``````prac_count <- data.frame(prac_count, row.names=1), counts<- prac_count[,1], rownames(counts) <- prac_count[,1], DGE1 <-DGEList(counts) `````` If doesn't work... have I missed a step? Thank you so much  
> **username_1**: That's not the code I gave in my answer, is it?  
> **username_1**: Don't mention it! Good luck with it.  

---

