<p>With things like MAS5, presence/absence calls were done using the P/M/A probe intensities and corresponded more to a "signal is reliable" p-value than literal presence/absence. This data is absent from the SOFT files, so you can't use the standard algorithms.</p>

<p>The only method left is to use "above X percentile of negative probes" as a cut-off for presence, which has been mentioned in a number of papersAFFX-BioB-3_at (e.g., <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3122888/" rel="nofollow noreferrer">here</a>). While there are a handful of control probes on that chip, I'm not aware of any of them being negative probes (or if there are any, there don't seem to be enough to be useful for this purpose). Thus I don't think you can even use this method.</p>

<p>Of course you can still do standard differential expression, even with GEO2R in the browser.</p>

CC BY-SA 3.0
2018-04-13T07:47:43.137Z
2018-04-13T07:47:43.137Z
Devon Ryan
<p>I would like to do a differential gene expression analysis on a microarray data.  From the literature, I understood, <strong>call detection (Present, Absent, Marginal)</strong> has to be done to minimize false positives. I found this <a href="http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/ProtocolSimpleaffy.txt" rel="nofollow noreferrer">tutorial</a> for the call detection and also to find the DEGs, <strong>from .cel files.</strong> </p>

<p>For this particular <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE837" rel="nofollow noreferrer">dataset</a> used for my study, <strong>.cel file is unavailable</strong> and only .txt file/ SOFT file is available for download. </p>

<ol>
<li>Can call detection be done from these files? </li>
<li>Or is there any other method/ package that can be used for the same?</li>
</ol>

CC BY-SA 3.0
2018-04-11T14:58:21.613Z
Without the .cel files one doesn't have expression data, so you can't analyse the dataset (although possibly in the .txt file there is a link to each .cel file). But you seem to be using GEO. Which is the ID of the dataset you are working with? Also showing how did you get to this point would help us to find the best way to help you.
llrs
CC BY-SA 3.0
2018-04-12T15:34:58.233Z
I have edited the question with more details.
Sunbiotech
CC BY-SA 3.0
2018-04-12T15:47:21.667Z
You haven't actually linked to a particular dataset, but SOFT files usually contain processed expression data, so you can skip right to DGE analysis. There should be details about how the expression data has been processed in the file metadata. There's a tutorial that goes through reading these files [here](https://warwick.ac.uk/fac/sci/moac/people/students/peter_cock/r/geo)
heathobrien
CC BY-SA 3.0
2018-04-12T21:03:44.893Z
I was about to comment that the edit wasn't enough, can you provide a link to the dataset or I misunderstood something?
llrs
CC BY-SA 3.0
2018-04-13T07:43:16.253Z
The data is accessible, look at the [GEO2R page](https://www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSE837) to download the dataset, under the tab "R script" you'll find the code to download the dataset. It is working for me.
llrs
<bioconductor><file-formats><differential-expression><microarray>
How to calculate call detection values in microarray datase if .cel file unavailable
# How to calculate call detection values in microarray datase if .cel file unavailable

(Asked by: username_0 on 2018-04-11)

I would like to do a differential gene expression analysis on a microarray data. From the literature, I understood, **call detection (Present, Absent, Marginal)** has to be done to minimize false positives. I found this [tutorial](http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/ProtocolSimpleaffy.txt) for the call detection and also to find the DEGs, **from .cel files.**

For this particular [dataset](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE837) used for my study, **.cel file is unavailable** and only .txt file/ SOFT file is available for download.

1. Can call detection be done from these files?
2. Or is there any other method/ package that can be used for the same?

**Tags:** bioconductor, file-formats, differential-expression, microarray
> **Comments:**
> **username_1**: Without the .cel files one doesn't have expression data, so you can't analyse the dataset (although possibly in the .txt file there is a link to each .cel file). But you seem to be using GEO. Which is the ID of the dataset you are working with? Also showing how did you get to this point would help us to find the best way to help you.  
> **username_0**: I have edited the question with more details.  
> **username_2**: You haven't actually linked to a particular dataset, but SOFT files usually contain processed expression data, so you can skip right to DGE analysis. There should be details about how the expression data has been processed in the file metadata. There's a tutorial that goes through reading these files [here](https://warwick.ac.uk/fac/sci/moac/people/students/peter_cock/r/geo)  
> **username_1**: I was about to comment that the edit wasn't enough, can you provide a link to the dataset or I misunderstood something?  
> **username_1**: The data is accessible, look at the [GEO2R page](https://www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSE837) to download the dataset, under the tab "R script" you'll find the code to download the dataset. It is working for me.  

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## 1 answers

### Answer by username_3 on 2018-04-13. Score: 0 | Accepted answer

With things like MAS5, presence/absence calls were done using the P/M/A probe intensities and corresponded more to a "signal is reliable" p-value than literal presence/absence. This data is absent from the SOFT files, so you can't use the standard algorithms.

The only method left is to use "above X percentile of negative probes" as a cut-off for presence, which has been mentioned in a number of papersAFFX-BioB-3\_at (e.g., [here](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3122888/)). While there are a handful of control probes on that chip, I'm not aware of any of them being negative probes (or if there are any, there don't seem to be enough to be useful for this purpose). Thus I don't think you can even use this method.

Of course you can still do standard differential expression, even with GEO2R in the browser.


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