<p>I am currently learning to perform Differential Analysis via DESEQ2 R Package, and I believe I've made progress, able to format the data correctly [maybe] for DDS(). When I run the results function to see the output, the data seems fine, as can be seen below:</p>
<pre><code>log2 fold change (MLE): Group RA vs C  Wald test p-value: Group RA vs
C  DataFrame with 6 rows and 6 columns
       baseMean log2FoldChange     lfcSE      stat    pvalue      padj
      &lt;numeric&gt;      &lt;numeric&gt; &lt;numeric&gt; &lt;numeric&gt; &lt;numeric&gt; &lt;numeric&gt; Gnai3   95.1978      0.3458366  0.275366  1.255916  0.209146  0.999383
Cdc45   21.9942     -0.0545177  0.346199 -0.157475  0.874870  0.999383
H19     29.0133     -1.4954220  1.516390 -0.986173  0.324048  0.999383
Narf    16.6967      0.2571059  0.370880  0.693232  0.488164  0.999383
Cav2    63.6356      0.5060019  0.354969  1.425480  0.154018  0.999383
Klf6    65.8469      0.2851175  0.265755  1.072858  0.283335  0.999383
</code></pre>
<p>However, when I run summary() or any other function, they do not seem to behave correctly, not counting any stats. Same with MAplot not coloring genes that should be marked red:</p>
<pre><code>out of 13184 with nonzero total read count adjusted p-value &lt; 0.1 LFC
&gt; 0 (up)       : 0, 0% LFC &lt; 0 (down)     : 0, 0% outliers [1]       : 150, 1.1% low counts [2]     : 0, 0% (mean count &lt; 1)
</code></pre>
<p>I'm confused as to why this is occurring and was wondering if anyone had ideas.</p>
<p>EDIT: Added More Code for context</p>
<pre><code>sergey &lt;- (read.csv(&quot;cleanmatrix25+.csv&quot;, sep = &quot;\t&quot;, header = T,
    check.names = F, row.names = &quot;Gene_names&quot;)) 

meta &lt;-(read.csv(&quot;metadata25+.csv&quot;, sep = &quot;\t&quot;, row.names = 1))
 
dds &lt;- DESeqDataSetFromMatrix(countData = sergey, colData = meta,
    design = ~Group)

keep &lt;- rowSums(counts(dds)) &gt;= 10 
dds &lt;- dds[keep,]

dds<span class="math-container">$Group &lt;- relevel(dds$</span>Group, ref = &quot;C&quot;)

dds &lt;- DESeq(dds)

res &lt;- results(dds)

head(res)

summary(res)

plotMA(res, ylim=c(-2,2))
</code></pre>
<p>EDIT2:</p>
<p>I sorted result by p-value, so all of these should be red on the following MAplot due to having a p-value &lt; 0.1</p>
<p><a href="https://i.sstatic.net/QhLwY.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/QhLwY.png" alt="enter image description here" /></a></p>
<p><a href="https://i.sstatic.net/klZPh.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/klZPh.png" alt="plotMA" /></a></p>

<r><deseq2>
DESEQ2 Question about results()
# DESEQ2 Question about results()

(Asked by: username_0 on 2021-08-10)

I am currently learning to perform Differential Analysis via DESEQ2 R Package, and I believe I've made progress, able to format the data correctly [maybe] for DDS(). When I run the results function to see the output, the data seems fine, as can be seen below:
log2 fold change (MLE): Group RA vs C  Wald test p-value: Group RA vs
C  DataFrame with 6 rows and 6 columns
       baseMean log2FoldChange     lfcSE      stat    pvalue      padj
                 Gnai3   95.1978      0.3458366  0.275366  1.255916  0.209146  0.999383
Cdc45   21.9942     -0.0545177  0.346199 -0.157475  0.874870  0.999383
H19     29.0133     -1.4954220  1.516390 -0.986173  0.324048  0.999383
Narf    16.6967      0.2571059  0.370880  0.693232  0.488164  0.999383
Cav2    63.6356      0.5060019  0.354969  1.425480  0.154018  0.999383
Klf6    65.8469      0.2851175  0.265755  1.072858  0.283335  0.999383

However, when I run summary() or any other function, they do not seem to behave correctly, not counting any stats. Same with MAplot not coloring genes that should be marked red:
out of 13184 with nonzero total read count adjusted p-value < 0.1 LFC
> 0 (up)       : 0, 0% LFC < 0 (down)     : 0, 0% outliers [1]       : 150, 1.1% low counts [2]     : 0, 0% (mean count < 1)

I'm confused as to why this is occurring and was wondering if anyone had ideas.
EDIT: Added More Code for context
sergey <- (read.csv("cleanmatrix25+.csv", sep = "\t", header = T,
    check.names = F, row.names = "Gene_names")) 

meta <-(read.csv("metadata25+.csv", sep = "\t", row.names = 1))
 
dds <- DESeqDataSetFromMatrix(countData = sergey, colData = meta,
    design = ~Group)

keep <- rowSums(counts(dds)) >= 10 
dds <- dds[keep,]

dds$Group <- relevel(dds$Group, ref = "C")

dds <- DESeq(dds)

res <- results(dds)

head(res)

summary(res)

plotMA(res, ylim=c(-2,2))

EDIT2:
I sorted result by p-value, so all of these should be red on the following MAplot due to having a p-value < 0.1

**Tags:** r, deseq2

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## 0 answers

