Differential expression between just 2 samples: a normal and a tumour sample from the same patient
Hi!
I am trying to perform some differencial expression analysis just to know which genes present different expression levels between a normal and a tumoral samples from the same patient. I have aligned and obtained gene counts with STAR and now I am trying to use DESeq2 to find differences between both samples. However, as I only have 1 sample for each group (tumour vs normal), DESeq2 is not working.
Do you know how can I achieve this goal?
Thanks!
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Statistics cannot be run with just 2 numbers - which is what you have per gene. Whatever you see could be purely by chance. You could manually calculate fold change and suggest a hypothesis, but you cannot back it up with any evidence - it is one of the design constraints of statistical analyses - they need at least 3 samples (per condition) for anything they say to make sense.
Hello jeni!
I am sorry to close this but this has been asked so many times before and it seems you have not invested the effort to read previous discussions, at least I do not see any specific question to any of the previously posted suggesteds in related threads. DESeq2 won't work for sure, for reference see an answer from the developer on the same question from just yesterday: https://support.bioconductor.org/p/p133710/
Some good explanation what DESeq2 does is offered here at HCB: https://hbctraining.github.io/DGE_workshop/lessons/04_DGE_DESeq2_analysis.html and this then probably will tell you why DESeq2 without replicates won't work. The technical minimum is a 2 vs 1 comparison, so one group must have a replicate while technically the other one does not, still this is far from being a well-powered experiment, but it is the technical minimum. More replicates = more power, simple as that. A 1 vs 1 is not robust at all and only of limited use e.g. for exploratory analysis.
Anyway, for suggestions on what you could do in terms of exploratory analysis please use the search function and google. This has been discussed extensively before, for example:
Analyzing RNA-seq without replicates
Advice on RNASeq analysis without biological replicates for differential gene expression.
DESeq2 (or EdgeR) Exploratory Analysis with no Replicates
best workflow for RNA data analysis without replications
If you have a specific question to any strategy after reading through the existing threads and suggestions then please add a comment, we might reopen this question then.
If you disagree please tell us why in a reply below, we'll be happy to talk about it.
Cheers!