<p>I see a lot of people using xCell. There should also be papers systematically compare many different methods, which might interest you.</p>

CC BY-SA 4.0
2020-06-24T07:45:26.550Z
Thanks for the pointer. Do you have any reference of a good up-to-date review paper? A simple description of the methods and requirements would be highly appreciated too
rvinas
CC BY-SA 4.0
2020-06-24T15:23:04.420Z
This one looks promising although it may not cover all the methods https://www.biorxiv.org/content/10.1101/2020.01.10.897116v1.full.pdf
Phoenix Mu
CC BY-SA 4.0
2020-06-23T21:14:31.323Z
2020-06-23T21:14:31.323Z
Phoenix Mu
<p>I would like to find the proportion of each cell-type in bulk RNA-Seq transcriptomics data. I am looking for some guidance on the following:</p>
<ul>
<li>What are the state-of-the-art methods?</li>
<li>What are their assumptions? (e.g. do they assume that cell-type expression signatures are available in advance?)</li>
</ul>

CC BY-SA 4.0
2020-06-23T11:50:07.643Z
Can you describe your experimental design further? This is often solved with single cell RNA-seq
Chris_Rands
CC BY-SA 4.0
2020-06-24T07:43:38.840Z
It's not my experiment - I am just trying to deconvolve bulk RNA-Seq data from a publicly available database (GTEx), e.g. given a whole blood sample, find out the proportions of each cell type (e.g. lymphocytes, macrophages,...). Any suggestion?
rvinas
<rna-seq><gene-expression><machine-learning>
What are the state-of-the-art cell-type RNA-Seq deconvolution methods?
# What are the state-of-the-art cell-type RNA-Seq deconvolution methods?

(Asked by: username_0 on 2020-06-23)

I would like to find the proportion of each cell-type in bulk RNA-Seq transcriptomics data. I am looking for some guidance on the following:

* What are the state-of-the-art methods?
* What are their assumptions? (e.g. do they assume that cell-type expression signatures are available in advance?)

**Tags:** rna-seq, gene-expression, machine-learning
> **Comments:**
> **username_1**: Can you describe your experimental design further? This is often solved with single cell RNA-seq  
> **username_0**: It's not my experiment - I am just trying to deconvolve bulk RNA-Seq data from a publicly available database (GTEx), e.g. given a whole blood sample, find out the proportions of each cell type (e.g. lymphocytes, macrophages,...). Any suggestion?  

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## 1 answers

### Answer by username_2 on 2020-06-23. Score: 1

I see a lot of people using xCell. There should also be papers systematically compare many different methods, which might interest you.

> **Comments:**
> **username_0**: Thanks for the pointer. Do you have any reference of a good up-to-date review paper? A simple description of the methods and requirements would be highly appreciated too  
> **username_2**: This one looks promising although it may not cover all the methods https://www.biorxiv.org/content/10.1101/2020.01.10.897116v1.full.pdf  

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