<p>According to <a href="https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#can-i-use-deseq2-to-analyze-a-dataset-without-replicates" rel="nofollow noreferrer">DESeq2</a>, you cannot analyze your data without having replicates.</p>
<p>In short, you have an experiment where you compare A to B because, in your theory, A is more expressed than B. However, you do the experiment only once. Without repeating the same experiment again under the same circumstances, there's no way to confirm you will have the same results and that your theory is correct.</p>
<p>You can still compare the ratio of <code>A/B</code> but that will not be meaningful in any way since there's not enough statistical power behind it. In your case, doing the ratio of <code>test1/test2</code>, <code>test2/test3</code> and <code>test1/test3</code>.</p>

CC BY-SA 4.0
2021-09-17T11:34:24.613Z
Thank you for the answer. Yes, right. So can I do the log2FC of "TPM value" of test/test2, test2/test/3 and test1/test3?
Juhee
CC BY-SA 4.0
2021-09-17T11:44:31.887Z
You can't really apply a `Log2FC` here since these values are not fold-changes. If you mean calculating the Log2 on the ratio of these values, you can do it, but it's only another way of representing your data. You have to be careful about the `0` since you cannot do `Log2(0) -> undefined`. Obviously, you also can't divide by 0 when performing the ratio. So you have to decide what to do with rows where there are `0`. If this answer satisfies your question, don't forget to accept the answer please.
user324810
CC BY-SA 4.0
2021-09-23T06:40:45.530Z
(just quick idea...) How about adding 1 to all the values to calculate Log2FC with TPM values?
Juhee
CC BY-SA 4.0
2021-09-17T10:58:28.853Z
2021-09-17T10:58:28.853Z
user324810
<p>I have three bulk RNA-seq samples (test1, test2, test3) without replicates.</p>
<p>And I noticed that DEG analysis tools such as DESeq2/edgeR/etc cannot be applied for data with no replicates.</p>
<p>So, I just drew a heatmap with expression value (TPM) of genes of interest, using NMF (aheatmap).</p>
<p>But now I want to perform DEG analysis across the three samples. Is there anything I can try for the analysis?</p>
<p>My TPM data (.csv) looks like below.</p>
<p><a href="https://i.sstatic.net/9nqEK.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/9nqEK.png" alt="enter image description here" /></a></p>
<p>Thank you so much.</p>

CC BY-SA 4.0
2021-09-17T09:41:26.853Z
Basically, you can’t do DEG analysis with no replicates in a way that will yield useful results.
user438383
<r><rna-seq>
Is it possible to do DEG analysis without replicates?
# Is it possible to do DEG analysis without replicates?

(Asked by: username_0 on 2021-09-17)

I have three bulk RNA-seq samples (test1, test2, test3) without replicates.

And I noticed that DEG analysis tools such as DESeq2/edgeR/etc cannot be applied for data with no replicates.

So, I just drew a heatmap with expression value (TPM) of genes of interest, using NMF (aheatmap).

But now I want to perform DEG analysis across the three samples. Is there anything I can try for the analysis?

My TPM data (.csv) looks like below.

[![enter image description here](https://i.sstatic.net/9nqEK.png)](https://i.sstatic.net/9nqEK.png)

Thank you so much.

**Tags:** r, rna-seq
> **Comments:**
> **username_1**: Basically, you can’t do DEG analysis with no replicates in a way that will yield useful results.  

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## 1 answers

### Answer by username_2 on 2021-09-17. Score: 2 | Accepted answer

According to [DESeq2](https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#can-i-use-deseq2-to-analyze-a-dataset-without-replicates), you cannot analyze your data without having replicates.

In short, you have an experiment where you compare A to B because, in your theory, A is more expressed than B. However, you do the experiment only once. Without repeating the same experiment again under the same circumstances, there's no way to confirm you will have the same results and that your theory is correct.

You can still compare the ratio of `A/B` but that will not be meaningful in any way since there's not enough statistical power behind it. In your case, doing the ratio of `test1/test2`, `test2/test3` and `test1/test3`.

> **Comments:**
> **username_0**: Thank you for the answer. Yes, right. So can I do the log2FC of "TPM value" of test/test2, test2/test/3 and test1/test3?  
> **username_2**: You can't really apply a `Log2FC` here since these values are not fold-changes. If you mean calculating the Log2 on the ratio of these values, you can do it, but it's only another way of representing your data. You have to be careful about the `0` since you cannot do `Log2(0) -> undefined`. Obviously, you also can't divide by 0 when performing the ratio. So you have to decide what to do with rows where there are `0`. If this answer satisfies your question, don't forget to accept the answer please.  
> **username_0**: (just quick idea...) How about adding 1 to all the values to calculate Log2FC with TPM values?  

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