Dear all,
thanks a lot for supporting such nice packages. I would like to know if limma fit function could be used with smaller set of genes or other metabolites quantified by liquid chromatography. I use limma in genes lists with thousand of genes, and never used with smaller features. I wonder if the moderated t-test could be used with only hundreds of features measured in small sample sets.
For instance, 2 or more groups; 4 biological replicates each, 150 genes/metabolites. Can we use empirical Bayes moderation in this situation? If yes that would be great, since limma provides an excelent tool to overcome unequal variances and normality deviation in cases like that.
Tks.
limma actually works on any number of genes at all. With just one or two genes, it will do linear modelling without empirical Bayes (EB) moderation.
In my lab, we use limma routinely on PCR data with as few as half a dozen genes. limma is careful to never use more df than one would get by pooling the genewise variances, and this prevents EB from overstating what can be learned from the gene ensemble.
Thanks! As far I could check all makes sense using limma with these small sets.