Answers.Body: <ol>
  <li>The fold changes for those are huge (on the order of 32x for the largest), so it's unsurprising for the adjusted p-values to be absurdly small.</li>
  <li>There's no reason to treat them differently.</li>
  </ol>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-11-27T15:09:37.247Z
Answers.LastActivityDate: 2020-11-27T15:09:37.247Z
Answers.UserDisplayName: Devon Ryan
Body: <p>After I got dds from my count matrix by DESeq(), I use results() method to get Padj and log2 fold changes for volcano plotting,
  then I found some gene's Padj values are infinite and the P-value is very close to 0;
  this makes those dots on my volcano plotting located very top to Y-aix and also confused me:</p>
  <ol>
  <li>is this normal or not, such a p-value (very close to 0) and -logPadj is infinite;</li>
  <li>how should I treat those data: are they very different expressed between samples and control or just abnormal data which should be taken off?</li>
  </ol>
  <p>Here follows the table:
  <a href="https://i.sstatic.net/Gju8a.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/Gju8a.png" alt="enter image description here" /></a></p>
  <p>table 1 is dds results, -log10(padj) show inf;
  table 2 is count matrix from featureCount
  table 3 is size factor of samples</p>
  <p>Please help me !</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-27T10:26:48.520Z
Comments.Text: It is not normal to get p-value close to zero, especially if you have not a lot of samples. If I look at your table 2, the mean counts don't tally with the genes in table 1... so can you sort this out
Comments.UserDisplayName: StupidWolf
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-27T10:28:48.247Z
Comments.Text: there are some instances, for example you knock out or over-express a gene, then of course you find this insanely differentially expressed..
Comments.UserDisplayName: StupidWolf
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-27T13:41:38.907Z
Comments.Text: The SE are really low in this case though, rather than huge LFC. Very consistent gene expression?
Comments.UserDisplayName: Greg
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-27T13:41:46.763Z
Comments.Text: For log(0) error add an arbitrarily small number to the 0 p.adj values (e.g.10^-99)
Comments.UserDisplayName: Greg
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-12-04T09:45:51.487Z
Comments.Text: @StupidWolf Thank you StupidWolf and Greg for answer my question. I didn't list all the samples out, and one of the compounds has the opposite effect from the others, like: d has a positive effect on empty control, and a b c has a negative effect on empty control; According to the answers, I think this may cause the so much differentially expressed(but i'm not so sure).
Comments.UserDisplayName: Chu
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-12-04T10:00:44.747Z
Comments.Text: what is being tested in this table? Hey our answers are as good as guesses if you just show a table. It's like reading the oracle from bones
Comments.UserDisplayName: StupidWolf
Tags: <rna-seq><deseq2>
Title: Question of Padj value (very high, infinite) got from dds
ThreadText: # Question of Padj value (very high, infinite) got from dds
  
  (Asked by: username_0 on 2020-11-27)
  
  After I got dds from my count matrix by DESeq(), I use results() method to get Padj and log2 fold changes for volcano plotting,
  then I found some gene's Padj values are infinite and the P-value is very close to 0;
  this makes those dots on my volcano plotting located very top to Y-aix and also confused me:
  
  1. is this normal or not, such a p-value (very close to 0) and -logPadj is infinite;
  2. how should I treat those data: are they very different expressed between samples and control or just abnormal data which should be taken off?
  
  Here follows the table:
  [![enter image description here](https://i.sstatic.net/Gju8a.png)](https://i.sstatic.net/Gju8a.png)
  
  table 1 is dds results, -log10(padj) show inf;
  table 2 is count matrix from featureCount
  table 3 is size factor of samples
  
  Please help me !
  
  **Tags:** rna-seq, deseq2
  
  > **Comments:**
  > **username_1**: It is not normal to get p-value close to zero, especially if you have not a lot of samples. If I look at your table 2, the mean counts don't tally with the genes in table 1... so can you sort this out  
  > **username_1**: there are some instances, for example you knock out or over-express a gene, then of course you find this insanely differentially expressed..  
  > **username_2**: The SE are really low in this case though, rather than huge LFC. Very consistent gene expression?  
  > **username_2**: For log(0) error add an arbitrarily small number to the 0 p.adj values (e.g.10^-99)  
  > **username_0**: @username_1 Thank you username_1 and username_2 for answer my question. I didn't list all the samples out, and one of the compounds has the opposite effect from the others, like: d has a positive effect on empty control, and a b c has a negative effect on empty control; According to the answers, I think this may cause the so much differentially expressed(but i'm not so sure).  
  > **username_1**: what is being tested in this table? Hey our answers are as good as guesses if you just show a table. It's like reading the oracle from bones  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_3 on 2020-11-27. Score: 1 | Accepted answer
  
  1. The fold changes for those are huge (on the order of 32x for the largest), so it's unsurprising for the adjusted p-values to be absurdly small.
  2. There's no reason to treat them differently.
  
  
  ---
  
  