DESeq2 normalization and TPM
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ribioinfo ▴ 90
@ribioinfo-9434
Last seen 13 months ago

Hello, I would like to ask two questions:

1) After using the DESeq2 normalization it is possible to compare the expression of the same gene among samples but it is not correct to compare different genes in the same samples. To do that is better to generate TPM but they are not as good as the DESeq2 nomalized values if you want to compare the expression of the same gene in different samples. Is the correct solution to generate two tables/heatmaps in order to have both the information or is there a better solution?

2) I would like to know how to interpret the normalized counts by DESeq2, for example how can I know if a x value, e.g. 10, means that the gene is high expressed or low expressed? Thank you.

deseq2 • 1.2k views
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@mikelove
Last seen 1 hour ago
United States

1) TPM is good for heatmaps, if you really want to compare expression values across genes, i.e. to say that a gene is more highly expressed than another. I would probably log10 transform to roughly stabilize the variance.

2) A normalized (or "scaled") count of 10 means that, if the sample you are looking at had been sequenced to similar depth as a sample with middle sequencing depth in this experiment, this gene would have had a count of 10.

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1) log2 or log10 TPM is the same right?

2) When you say normalized or "scaled" are talking about the values normalized with the DESeq2 normalization that uses the geometric mean and median of the ratio? In this case why it is not better to use the log2 of them (since this normalization is designed for the purpose to compare a gene among samples) instead of the log2 TPM?

Thank you.

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