This is a test version of Biostars. For the public version, visit https://www.biostars.org.
RNA-seq Differential Expression Analysis

Hello all

I am currently working with some sequences (with no replication), and I have been trying to find a way to report the results with no success, is there any standard way to do it (type of graphs, data to be shown, etc)? I would also appreciate any kind of papers that can be used as guide.

rna-seq r edger

Honestly, with no replication the results will be largely useless. Do you have more than two total samples/groups?

I have 4 different tissues, so I guess they could be considered as groups

When you do not have replicates, it is better to go by ranking using fold change information. You can try GFOLD as Devon Ryan mentioned.

Suggestion: Anyways for better result we need replicates.

2 answers

Keeping in mind that the statistics are questionable, the worthwhile graphs would include the results from hierarchical clustering of the samples/groups. I suppose you could make a PCA plot, though that'd probably be no more interpretable than the clustering (though it's easy enough to do). I'd skip the stereotypical MA plot with unreplicated data.

You can use DEGseq package to analyze. There are three method to choice for Differential Expression. DEGseq is a package in R.

One should keep in mind that the statistical model used in DEGseq is wrong and the results from it will be even less useful than those from GFOLD, which is probably one of the better tools to use in cases like this.

Hi Ryan, could you give a little detailed explaination why the model in DEGSeq is not correct. This package was published on journal and cited more 100 times in past few years. Thank you.

Log in to answer this question.