Third quartile normalized logFC data to find differentially express gene using limma

Question

[Nai]

I have normalized count matrix which is normalized using conditional quantile normalization and having negative value, I understand that these are normalized logFC values. When I am directly using into limma with following command. It is showing error. The steps:

data <- read.csv("new_count_arranged.csv", sep = ';') meta_data <- read.csv("new_pheno_sorted_comma.csv", sep = ';') y <- normalizeBetweenArrays(data)

Error in normalizeBetweenArrays(dbgap_data) : 'object' is a data.frame and not all columns are numeric

Kindly help to caluculate pvalue , padjusted value, TPM

File Format:

geneid sample1 sample2 AB1 3.09852052 9.07170501 CBF 5.30616784 -0.06336533

[Basti]

You must convert data to a numeric matrix as indicated by the error

[Nai]

Can you guide me about me, because when I converted it then it showed, not all columns are integers. I request for help to perform this. I am using limma first time.

[Basti]

I think a quick search on Google "convert dataframe to numeric r" or alternatives would give you an answer