Hi,
I am currently struggling with analysing my RNA-seq data. We have RNA-seq data from a variety of patients and we want to look at genes that change in expression with respect to variable such as fatmass, muscle mass, weight, etc. Variable all of which are continuous.
I have previously used edgeR to analyse RNA-seq data, but the data I had was divided into two groups, obese and lean, and I could determine differentially expressed genes between the two groups.
I have looked at edgeR's glm function, but as I am not very familiar with stats, I am struggling to understand it and whether it would be useful in the analysis I want to carry out. So we want to do something similar to linear regression in R and look at whether the expression of genes decreases/increases with an increase/decrease in the different variables (e.g. weight).
Does anyone have any experience in this and able to help me out?
Thanks
Elie
I am currently struggling with analysing my RNA-seq data. We have RNA-seq data from a variety of patients and we want to look at genes that change in expression with respect to variable such as fatmass, muscle mass, weight, etc. Variable all of which are continuous.
I have previously used edgeR to analyse RNA-seq data, but the data I had was divided into two groups, obese and lean, and I could determine differentially expressed genes between the two groups.
I have looked at edgeR's glm function, but as I am not very familiar with stats, I am struggling to understand it and whether it would be useful in the analysis I want to carry out. So we want to do something similar to linear regression in R and look at whether the expression of genes decreases/increases with an increase/decrease in the different variables (e.g. weight).
Does anyone have any experience in this and able to help me out?
Thanks
Elie
