I have a gene expression matrix from RNA-seq as
gene Individual1 Individual2 Gene1 77.9 89.7 Gene2 67.5 14.8
From RNA-seq data, I performed normalization which is represented by the values as 77.9 etc. In the matrix, genes are in rows, columns have samples with FPKM values for each gene across the samples. I want to run a linear mixed effect model to calculate p-vlaues for each gene across all the samples. I want to run a linear mixed model like:
Model = lmer(FPKM ~ (1|gene), data=X)
I am getting an error as there is no variable called FPKM. However, the FPKM values are represented in a matrix for each individual in the columns for each gene. I need help to run the model to generate p-values for each gene across the samples. I will appreciate any help. Thank you!