I would like to do a Fisher's exact test 2x2 for each gene on my list (see picture) to statistically check if there are any differences in frequencies, for each gene, between the two compared groups (i.e., M1 and M2). Due to the big number of genes, I can't mount manually a contingency table for each one and calculate the Fischer test individually. Could you please inform me about the R codes to calculate the Fisher's p-value for each of the genes in an easier and faster way?

Example_My List

data=structure(list(M1 = c(0.87, 0.93, 0.8, 0.53, 0.27, 0.53, 0.93, 
0.6, 0.93, 0.8, 1, 0.93, 0.87, 0.73, 1, 0.47, 1, 0.87, 0.47, 
0.27), M2 = c(0.76, 0.71, 0.19, 0.52, 0.33, 0.67, 0.9, 0.71, 
0.81, 1, 0.76, 0.14, 0.9, 1, 0.9, 0.81, 0.95, 0.43, 0.86, 0.14
)), row.names = c("Phvul.001G002900", "Phvul.001G003000", "Phvul.001G006300", 
"Phvul.001G007400", "Phvul.001G008300", "Phvul.001G009600", "Phvul.001G011300", 
"Phvul.001G012300", "Phvul.001G012700", "Phvul.001G012800", "Phvul.001G013200", 
"Phvul.001G013400", "Phvul.001G015000", "Phvul.001G016600", "Phvul.001G018600", 
"Phvul.001G021550", "Phvul.001G024300", "Phvul.001G025300", "Phvul.001G027900", 
"Phvul.001G030400"), class = "data.frame")