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Identify Differentially Expressed Genes With Two Groups In Which There Are Only Two Replicates

Hello everyone,

I want to Identify differentially expressed genes with two groups in which there are only two replicates.

What methods should I use? I want to use t-statistics or Mann- Whitney test, but I am not sure the minimum replicates of the t-statistics or Mann- Whitney test.

Thank you

microarray differential-expression

Can you clarify your question? You say you have two replicates, which suggests that you have four samples (2 groups x 2 replicates = 4). Or do you have two groups with 0 replicates -- ie. you have 2 samples.

Also, your tag says "microarray" but it is not mentioned in your question what platform you have used for expression measurement. Can you please further modify your question to specify if that this is microarray (vs. rna-seq, for example)?

Ok.I have four samples(2 groups x 2 replicates).The platform I used is Affymetrix GeneChip Mouse Genome 430A 2.0. Could I use Mann- Whitney test?

well minimum sample size for t-test is 2 (for which the degree of freedom = 1), but the statistics won't be very reliable.

Thank you! What about Mann- Whitney test?

it can be performed too. but in general smaller the sample size, less reliable will be the result. .

What kind of replicates? Biological replicates? Technical replicates?

If you only have technical replicates, then it does not make sense to use a statistical test. What you will pick up will be technical differences, and not biological differences. Even if they are biological replicates, I would be very skeptical of ANY results produced with only 2 replicates. It may work well for a pilot study to asses whethere there was enough RNA in a given sample or likewise, but the biological conclusions you can draw from such a dataset if very limited.

Many thanks for your advice.

1 answer

Unless you have a very good reason not to do so, your first preference for any microarray analysis should always be limma.

There is an extensive user's guide which is very much worth reading, as well, before you start your analysis.

Thank you.I have read it.

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