Answers.Body: <p>You ask about which &quot;genes are expressed&quot; and then you mention &quot;if a gene is up or down regulated&quot;. These are different, and given your application I think what you actually want to know if these marker genes are expressed. This is not a question of up/down-regulation relative to a control, so you do not need control samples for this.</p>
  <p>It seems most of your datasets are Affymetrix, and there are R/Bioconductor packages that will give you the probability a gene is expressed. One such I found is frma (<a href="https://bioconductor.org/packages/release/bioc/html/frma.html" rel="nofollow noreferrer">https://bioconductor.org/packages/release/bioc/html/frma.html</a>), which returns an object &quot;weight&quot; that is &quot;a vector of weights which roughly correspond to the probability of expression for each gene.&quot; I haven't worked with microarrays in a while, but I recall many other R/Bioconductor packages offering this functionality.</p>
  <p>A detection p-value is calculated for Illumina array probes in Illumina's native BeadStudio software.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-01-21T01:09:41.153Z
Answers.LastActivityDate: 2021-01-21T01:15:16.717Z
Answers.LastEditDate: 2021-01-21T01:15:16.717Z
Answers.UserDisplayName: user1799035
Body: <p>I have a microarray gene expression dataset consisting of placenta samples. I want to check whether these placenta samples are mixed with maternal decidua tissue. I have marker genes for decidua samples SCARA5, PIGF, SLPI. How to check whether these genes are expressed in placenta samples? In other words, how to check if a gene is up or down regulated without control group?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-14T11:05:55.563Z
Comments.Text: Which microarray? Some have negative controls that can be used to assess the probability that a gene/transcript is expressed.
Comments.UserDisplayName: Devon Ryan
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-14T21:45:23.087Z
Comments.Text: I look at theese datasets: GSE73374, GSE73685, GSE9984, GSE122214, GSE22490, GSE35574, GSE37901. The microarray platforms are Affymetix and Illumina: affy_hugene_2_0_st_v1, affy_hugene_1_0_st_v1, affy_hg_u133_plus_2, illumina_humanwg_6_v2. Unfortunately I do not have access to illumina raw data, only to the preprocessed one. Can I still get negative controls from it?
Comments.UserDisplayName: Sashko Lykhenko
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-16T14:23:04.687Z
Comments.Text: At least some of those have the .CEL files included, so you have all of the data.
Comments.UserDisplayName: Devon Ryan
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-16T16:04:25.300Z
Comments.Text: @DevonRyan I've looked .CELL files' description and indeed there are control probes. Could you give me a hint, how do I move from these raw data to the lists of up- and down-regulated genes?
Comments.UserDisplayName: Sashko Lykhenko
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-16T16:48:11.030Z
Comments.Text: Finding up and down regulated genes requires using R packages like affy and limma. Please search for tutorials.
Comments.UserDisplayName: Devon Ryan
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-16T19:48:43.717Z
Comments.Text: Thank you @DevonRyan I will look them up more closely. But aren't these methods require having case and control groups of samples and not just one group like in my case?
Comments.UserDisplayName: Sashko Lykhenko
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-16T19:50:08.337Z
Comments.Text: Your previous comment asked for up and down-regulated genes. That requires some sort of treatment groups, yes.
Comments.UserDisplayName: Devon Ryan
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-01-16T19:56:17.187Z
Comments.Text: Oh, I see now. I said up- and down-regulated, but I meant expressed and unexpressed relative to control probes. My bad.
Comments.UserDisplayName: Sashko Lykhenko
Tags: <gene-expression><transcriptome><microarray>
Title: How to check if a given gene is expressed in a group of microarray samples if I do not have control group to compare with?
ThreadText: # How to check if a given gene is expressed in a group of microarray samples if I do not have control group to compare with?
  
  (Asked by: username_0 on 2021-01-13)
  
  I have a microarray gene expression dataset consisting of placenta samples. I want to check whether these placenta samples are mixed with maternal decidua tissue. I have marker genes for decidua samples SCARA5, PIGF, SLPI. How to check whether these genes are expressed in placenta samples? In other words, how to check if a gene is up or down regulated without control group?
  
  **Tags:** gene-expression, transcriptome, microarray
  
  > **Comments:**
  > **username_1**: Which microarray? Some have negative controls that can be used to assess the probability that a gene/transcript is expressed.  
  > **username_0**: I look at theese datasets: GSE73374, GSE73685, GSE9984, GSE122214, GSE22490, GSE35574, GSE37901. The microarray platforms are Affymetix and Illumina: affy_hugene_2_0_st_v1, affy_hugene_1_0_st_v1, affy_hg_u133_plus_2, illumina_humanwg_6_v2. Unfortunately I do not have access to illumina raw data, only to the preprocessed one. Can I still get negative controls from it?  
  > **username_1**: At least some of those have the .CEL files included, so you have all of the data.  
  > **username_0**: @username_1 I've looked .CELL files' description and indeed there are control probes. Could you give me a hint, how do I move from these raw data to the lists of up- and down-regulated genes?  
  > **username_1**: Finding up and down regulated genes requires using R packages like affy and limma. Please search for tutorials.  
  > **username_0**: Thank you @username_1 I will look them up more closely. But aren't these methods require having case and control groups of samples and not just one group like in my case?  
  > **username_1**: Your previous comment asked for up and down-regulated genes. That requires some sort of treatment groups, yes.  
  > **username_0**: Oh, I see now. I said up- and down-regulated, but I meant expressed and unexpressed relative to control probes. My bad.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2021-01-21. Score: 3 | Accepted answer
  
  You ask about which "genes are expressed" and then you mention "if a gene is up or down regulated". These are different, and given your application I think what you actually want to know if these marker genes are expressed. This is not a question of up/down-regulation relative to a control, so you do not need control samples for this.
  
  It seems most of your datasets are Affymetrix, and there are R/Bioconductor packages that will give you the probability a gene is expressed. One such I found is frma (<https://bioconductor.org/packages/release/bioc/html/frma.html>), which returns an object "weight" that is "a vector of weights which roughly correspond to the probability of expression for each gene." I haven't worked with microarrays in a while, but I recall many other R/Bioconductor packages offering this functionality.
  
  A detection p-value is calculated for Illumina array probes in Illumina's native BeadStudio software.
  
  
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