Hey there! Hope everyone is doing well :)
I have a question regarding using LIMMA package for data that is not RNA-seq nor microarray. I have a dataset of protein/biomarker quantification(around 365 proteins) and I would like to get log-fold changes(i.e. using differential protein expression) based on my conditions of interest. However, the used measurement technique for the dataset I have(Proximity Extension Assay technology) does not provide absolute expression/quantification, but normalized protein expression (NPX). NPX(click here for more details) is an arbitrary unit on Log2 scale. These normalized expressions(their expressions are normally distributed) are highly correlated with absolute quantification of proteins(spearman's correlation can reach up to 0.85 for the same proteins).
My understanding is since the data that I have is normalized quantification/expression, which is similar to what is done in microarrays(normalized Microarray intensity values), the data I have can be analyzed using the same pipelines for microarrays. However, in the user guide of limma, I could not find an explanation/mention about whether limma could also be used in such settings/data/applications.
My questions are :
1) is it possible to use limma to find differentially expressed proteins in my case? Also, is it a valid way for such analysis?
2) if yes, should I also set
trend=T and robust =T or just use the normal pipeline?
3) if that's not possible, any thoughts or suggestions to do differential protein expression?
Thank you very much in advance for your help!
NOTE: this question has already been posted in BIOSTARS, but reposted here after a suggestion from ATpoint