Dear community,

I am currently trying to figure out this question. I have tried different keywords but I do not seem to find the right thread. 

What I want to know is:

- Does limma arrives to a pvalue by using the log2 scale of the normalized array data?

- Does limma arrives to a pvalue using the normalized array data directly and then shows the differences as log2 fold changes in the top table?

If you know the proper thered to refer to, that will be of great help, else, I am grateful for your responses.

Thanks!

limma - or specifically, lmFit and its downstream functions - will operate on whatever matrix of values you give it. If you're working with microarray data, then - as svlachavas has mentioned - you should be giving lmFit the log-transformed intensities, for various reasons. lmFit will not log-transform the values for you, as it assumes that's already been done. Thus, it's worth checking what was done upstream to ensure that limma is running on the correct values. For example, if you're using normalizeBetweenArrays before running lmFit, then the former function will log-transform the data if your input is an EListRaw object, but not if your input is a matrix. (Specifically, the function returns normalized log-transformed intensities, so there's no distinction between normalization and log-transformation in all of the downstream functions.) In summary, assuming you've done the analysis correctly, then the p-values from limma will be computed from the log-intensities.

Dear Serpalma,

i don't know where you heard or read anything about "linear values" ? Or also to which technology you refer to ? For instance about microarray gene expression data, topTable() from limma provides log2 fold changes ("effect sizes") about your comparisons of interest, along with the relative p-values . But for more specific details and not generalizations, you should definately read the 2 papers below:

1)  http://www.statsci.org/smyth/pubs/ebayes.pdf

2) http://www.ncbi.nlm.nih.gov/pubmed/25605792

Hope that solves any general questions

Best,

Efstathios