Answers.Body: <p>I cannot think of a way without performing differential expression analysis. Since you don't have controls, what you could do is assigning some of the samples as controls.</p>
  <p>Let's say you have samples A, B, C, D, E and F. You can perform differential expression analysis A, B, C (i.e. treatment) versus D, E (control). If you perform this for all possible combinations (that would be 5 choose 2 which is equal to 5 choose 3 if you decide to go for 3 vs 2 splits) and filter for genes which do not show up in any DE list you end up with the genes that are expressed similarly in al of these samples.</p>
  
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Answers.CreationDate: 2020-10-12T16:30:56.613Z
Answers.LastActivityDate: 2020-10-12T16:30:56.613Z
Answers.UserDisplayName: haci
Body: <p>I have 5 samples (from a RNA seq experiment) from patients but I have no control, so since we can't look for the differentially expressed genes we want to look for the genes that have similar expression in all the sample.
  We want to do that to see if some genes that can be involved are among those expressed in all the samples.
  I have never done that, I do not know how to do it and I cant find any info about it, so any ideas are welcome.</p>
  <p>Thanks!</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-10-08T19:57:33.393Z
Comments.Text: Genes "that are expressed the same" would be "the genes that are NOT differentially expressed" so if you cannot study the latter you cannot study the former.
Comments.UserDisplayName: haci
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-10-09T12:38:24.780Z
Comments.Text: Please [edit] your question and give us some details. Do you already have expression data? What data do you have? What kind of format are they in? Why would you look at all genes that are similarly expressed in all samples? That won't help you identify genes related to a phenotype, not without a control.
Comments.UserDisplayName: terdon
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-10-09T16:37:02.697Z
Comments.Text: standard deviation/mean?
Comments.UserDisplayName: Greg
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Comments.CreationDate: 2020-10-12T14:57:13.847Z
Comments.Text: I have edit the question, I hope now is more clear. thanks!
Comments.UserDisplayName: Mee
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-10-12T17:11:50.903Z
Comments.Text: Uhm... if your patients are humans I guess you can find controls on the Internet.
Comments.UserDisplayName: juanjo75es
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-10-12T17:15:41.653Z
Comments.Text: If they are not humans (!!) then you don't need differential expression analysis. Just make expression analysis and then make a script to select transcripts that are equally expressed. It's only a few lines in any language. I would use python for that.
Comments.UserDisplayName: juanjo75es
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-10-13T07:44:14.160Z
Comments.Text: Patients are humans but It is not easy to find controls on the Internet since the protocol and the sequencing has to be done exactly the same way,
Comments.UserDisplayName: Mee
Tags: <gene-expression>
Title: Looking for genes that are expressed the same in all the samples
ThreadText: # Looking for genes that are expressed the same in all the samples
  
  (Asked by: username_0 on 2020-10-08)
  
  I have 5 samples (from a RNA seq experiment) from patients but I have no control, so since we can't look for the differentially expressed genes we want to look for the genes that have similar expression in all the sample.
  We want to do that to see if some genes that can be involved are among those expressed in all the samples.
  I have never done that, I do not know how to do it and I cant find any info about it, so any ideas are welcome.
  
  Thanks!
  
  **Tags:** gene-expression
  
  > **Comments:**
  > **username_1**: Genes "that are expressed the same" would be "the genes that are NOT differentially expressed" so if you cannot study the latter you cannot study the former.  
  > **username_2**: Please [edit] your question and give us some details. Do you already have expression data? What data do you have? What kind of format are they in? Why would you look at all genes that are similarly expressed in all samples? That won't help you identify genes related to a phenotype, not without a control.  
  > **username_3**: standard deviation/mean?  
  > **username_0**: I have edit the question, I hope now is more clear. thanks!  
  > **username_4**: Uhm... if your patients are humans I guess you can find controls on the Internet.  
  > **username_4**: If they are not humans (!!) then you don't need differential expression analysis. Just make expression analysis and then make a script to select transcripts that are equally expressed. It's only a few lines in any language. I would use python for that.  
  > **username_0**: Patients are humans but It is not easy to find controls on the Internet since the protocol and the sequencing has to be done exactly the same way,  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2020-10-12. Score: 1 | Accepted answer
  
  I cannot think of a way without performing differential expression analysis. Since you don't have controls, what you could do is assigning some of the samples as controls.
  
  Let's say you have samples A, B, C, D, E and F. You can perform differential expression analysis A, B, C (i.e. treatment) versus D, E (control). If you perform this for all possible combinations (that would be 5 choose 2 which is equal to 5 choose 3 if you decide to go for 3 vs 2 splits) and filter for genes which do not show up in any DE list you end up with the genes that are expressed similarly in al of these samples.
  
  
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