Hi, I am using lmFit in R. I am new to R, lmFit and study context, and I highly appreciate your input.
The study concerns which of 150 proteins show different mean values between 2 groups (like cases and controls). Our data are comprised as: 500 rows for 500 unique individuals, and 151 columns for 150 proteins and 1 variable for the 2-level group variable (control=0, case=1).
I have used the R codes that Hamel Patel (2021) Scientific Reports and published at: https://zenodo.org/record/3895886#.YJKg893RbDc I refrain from pasting the codes here as I am not sure whether it is allowed, but the authors made it freely available. Since I am not used to every aspect of this work, I have asked statisticians to verify my script and they assured that I am using correctly given the data.
My question concerns the second part of our study. We have a set of 4 proteins (ie, column variables) derived from another context. We would like to examine whether these 4 proteins are different by the 2 level groups (case vs control). The sample size, 500, remains the same.
Given that lmFit can utilise variance information across dependent variables (ie, 4 proteins), I consider that the use of lmFit is better than analysing each of 4 proteins one by one by linear regressions. However, because 4 proteins would be much smaller number than usual application of lmFit, I would like to ask for your input if there is reasons that lmFit may not be suitable.
Thank you for your time for my questions, in advance.