Hi, I have a question about how to do covariate adjustment. I have two sets of 'gene expression' data. They are from two different tissue types, 'liver' and 'brain', respectively. The purpose of my analysis is to compare the pattern of the whole genome 'gene expression' between the two tissue types. I have 'age' and 'sex' as covariates. Since 'age' and 'sex' definitely have influence on gene expression, I need to first filter out the proporation of 'gene expression' attributable to 'age' and 'sex', then compare the 'remaining gene expression' value between 'liver' and 'brain'. How to do the covariate adjustment to remove the effects of these two covariates? Should I do a 'step-wise' regression or something? Which function in R should I use?
I am new to this field, and really appreciate your help! thank you very much, karena -- View this message in context: http://r.789695.n4.nabble.com/How-to-do-covariate-adjustment-in-R-tp3537463p3537463.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
