<p>DESeq2 works for that.  Unless you literally have only two samples.</p>
<p>There is <strong>no</strong> statistically sound way of analyzing DE genes with literally only two samples.  This is a bad experimental design, suitable for only the roughest of exploratory purposes.  Only the most obvious differences (that you probably knew already) are likely to be borne out in a legitimate experiment.</p>

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2021-11-03T06:07:38.290Z
2021-12-04T06:09:26.820Z
2021-12-04T06:09:26.820Z
swbarnes2
<p>We have an RNA seq taken from a the same tissue in two different developmental stages. We have one gene, with the number of reads from stage A and stage B, and we want to see which genes are differentially expressed.</p>
<p>After performing RNA-seq, I am left with a CSV file containing a list of genes and the amount of reads in two different cell types. We have one list of genes, with the number of reads in Stage A in one column and the number of reads in Stage B in another column. We are looking to see what types of genes are differentially expressed in the two stages.</p>
<p>I have used DESeq2, but I'm not sure if this is the best/correct to analyze what I am looking for.</p>
<p>What is the best package to analyze the data for significant differential gene expression?</p>
<p>Thanks</p>

<rna-seq><deseq2>
Best R program to use for RNA seq analysis
# Best R program to use for RNA seq analysis

(Asked by: username_0 on 2021-11-02)

We have an RNA seq taken from a the same tissue in two different developmental stages. We have one gene, with the number of reads from stage A and stage B, and we want to see which genes are differentially expressed.

After performing RNA-seq, I am left with a CSV file containing a list of genes and the amount of reads in two different cell types. We have one list of genes, with the number of reads in Stage A in one column and the number of reads in Stage B in another column. We are looking to see what types of genes are differentially expressed in the two stages.

I have used DESeq2, but I'm not sure if this is the best/correct to analyze what I am looking for.

What is the best package to analyze the data for significant differential gene expression?

Thanks

**Tags:** rna-seq, deseq2

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## 1 answers

### Answer by username_1 on 2021-11-03. Score: 1

DESeq2 works for that. Unless you literally have only two samples.

There is **no** statistically sound way of analyzing DE genes with literally only two samples. This is a bad experimental design, suitable for only the roughest of exploratory purposes. Only the most obvious differences (that you probably knew already) are likely to be borne out in a legitimate experiment.


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