<p>In the TCGA datasets there is a variable (type) containing the information if the sample was from the tumor or from an adjacent region, which is usually considered as healthy. </p>

<p>As this samples come from the same patient and the same tissues they are used in the analysis for the comparisons and classifications.</p>

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2017-12-04T09:51:04.930Z
2017-12-04T09:51:04.930Z
llrs
<p>Assume I want to run a simple machine learning of healthy/non healthy classification, how can I use <a href="https://cancergenome.nih.gov/cancersselected" rel="nofollow noreferrer">TCGA</a> where it has only data of people with cancer. What do usually people do for example for study of gene expressions?</p>

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2017-12-03T17:17:41.833Z
Depends. What do you want to study? Genome architecture? Gene expression? Cell structure? Metabolic rate? Variants? Usually, you would compare the healthy to non healthy sample from the same individual but we can't really answer unless you specify what sort of analysis you want to do.
terdon
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2017-12-03T17:18:43.117Z
@terdon gene expression. But TCGA doesn't contain healthy cells of the same person.
0x90
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2017-12-03T17:20:03.120Z
@terdon my final goal is to do metabolic analysis, but I need to do gene expression first.
0x90
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2017-12-03T21:11:31.567Z
In cancer research with gene expression profiling, you can find molecular subtypes with machine learning. These subtypes are usually not seen with the standard pathological methods. [Here](https://www.ncbi.nlm.nih.gov/pubmed/11823860) is a famous study where they define a different subtype of breast cancer, that respond differently to therapy. With this gene signature they can identify patients that do not benefit from a certain therapy, but would survive without it (you save them a lot of side effects which come with the therapy).
benn
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2017-12-04T07:44:57.777Z
Consider that is hard to justify to an ethic committee to remove a healthy tissue with an operation for the purpose of acquire data.
llrs
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2017-12-04T08:45:41.617Z
Now that I was looking for an analysis in the TCGA data, AFAIK it has data of the same people but from healthy regions (near the tumoral regions), which is usually considered as healthy. I suspect that this samples are the ones used for ML. In the TCGA datasets there is a variable  `type` used to encode if the sample is a "tumor" or "normal".
llrs
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2017-12-04T08:50:30.997Z
@Llopis that what I thought, but I didn't see the healthy tissue sample there. Can you post an example.
0x90
CC BY-SA 3.0
2017-12-04T09:01:39.937Z
[This](http://llrs.github.io/IEO/IEO_report.html) was an analysis for my master. See Figure 3.A. I didn't download the data, which was provided as a summarized experiment object of Bioconductor. But I would expect to be downloadable somehow.
llrs
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2017-12-04T09:04:35.643Z
@Llopis thanks. Feel free to add it as an answer. Did you write you thesis in jupyter or just the SI part?
0x90
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2017-12-04T09:22:43.010Z
That is only a project for one subject and it was written in rmarkdown. My master thesis was like an article and I used MS Word. I still have to learn  jupyter.
llrs
<database><cancer>
What would be a reasonable healthy data set/control group to compare with a cell line from TCGA?
# What would be a reasonable healthy data set/control group to compare with a cell line from TCGA?

(Asked by: username_0 on 2017-12-03)

Assume I want to run a simple machine learning of healthy/non healthy classification, how can I use [TCGA](https://cancergenome.nih.gov/cancersselected) where it has only data of people with cancer. What do usually people do for example for study of gene expressions?

**Tags:** database, cancer
> **Comments:**
> **username_1**: Depends. What do you want to study? Genome architecture? Gene expression? Cell structure? Metabolic rate? Variants? Usually, you would compare the healthy to non healthy sample from the same individual but we can't really answer unless you specify what sort of analysis you want to do.  
> **username_0**: @terdon gene expression. But TCGA doesn't contain healthy cells of the same person.  
> **username_0**: @terdon my final goal is to do metabolic analysis, but I need to do gene expression first.  
> **username_2**: In cancer research with gene expression profiling, you can find molecular subtypes with machine learning. These subtypes are usually not seen with the standard pathological methods. [Here](https://www.ncbi.nlm.nih.gov/pubmed/11823860) is a famous study where they define a different subtype of breast cancer, that respond differently to therapy. With this gene signature they can identify patients that do not benefit from a certain therapy, but would survive without it (you save them a lot of side effects which come with the therapy).  
> **username_3**: Consider that is hard to justify to an ethic committee to remove a healthy tissue with an operation for the purpose of acquire data.  
> **username_3**: Now that I was looking for an analysis in the TCGA data, AFAIK it has data of the same people but from healthy regions (near the tumoral regions), which is usually considered as healthy. I suspect that this samples are the ones used for ML. In the TCGA datasets there is a variable  `type` used to encode if the sample is a "tumor" or "normal".  
> **username_0**: @Llopis that what I thought, but I didn't see the healthy tissue sample there. Can you post an example.  
> **username_3**: [This](http://llrs.github.io/IEO/IEO_report.html) was an analysis for my master. See Figure 3.A. I didn't download the data, which was provided as a summarized experiment object of Bioconductor. But I would expect to be downloadable somehow.  
> **username_0**: @Llopis thanks. Feel free to add it as an answer. Did you write you thesis in jupyter or just the SI part?  
> **username_3**: That is only a project for one subject and it was written in rmarkdown. My master thesis was like an article and I used MS Word. I still have to learn  jupyter.  

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## 1 answers

### Answer by username_3 on 2017-12-04. Score: 2

In the TCGA datasets there is a variable (type) containing the information if the sample was from the tumor or from an adjacent region, which is usually considered as healthy.

As this samples come from the same patient and the same tissues they are used in the analysis for the comparisons and classifications.


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