How to find Mann-whitney p value across all genes using R?

Question

I need to perform mann-whitney test across all genes using R programming. I need to input a text file where first row contains samples, second row contains cohort variables (1 or 2),all other rows contains the gene expressions. This I need to do using function.

The output at the end should be a table with the results: genes in the rows, columns with mean expression of cohort 1, mean expression of cohort 2, FC and mann-whitney p value.

This is what I tried using a demo data but it doesn't seem to be working. I get only G4 as gene in the row and "NAN" without any values in the rows for columns of mean expression of cohort 1, mean expression of cohort 2, FC and mann-whitney p value

data <- read.table(text = "
Cohort  Gene    S1  S2  S3  S4  S5
1   G1  1389    1097    1501    4630    2011
2   G2  1023    880 492 4411    1233
1   G3  2847    2717    2814    4145    5433
2   G4  20612   18123   17679   4099    8567
", header = TRUE)


#separate cohort 1 and 2
cohort1<-data[data$Cohort != "2", 1]
#head(cohort1)
cohort2<-data[data$Cohort != "1", 1]

geneNames <- data$Gene
row.names(data) <- data$Gene

df <- data.frame()

for (Gene in 1:length(geneNames)){
  
  if (sum(cohort1) | sum(cohort2) > 0){
    mwt <- wilcox.test(x = cohort1, y = cohort2, paired = T, exact = F, conf.int = F)
  } else if (sum(cohort1) | sum(cohort2) == 0){
    mwt <- data.frame("p.value" = NA, "conf.int" = NA)
  }
  
  table <- data.frame("Gene" = geneNames[Gene],"Mean_Cohort1" = mean(cohort1),
                      "Mean_Cohort2" = mean(cohort2),"FC" = mean(cohort1)/mean(cohort2), "MW_Pvalue" = mwt$p.value)
  output <- rbind(df, table)
  
  
}

Can anybody help me out with this?