R - Multiple chi square test on dataframe per row - get results same dataframe

Question

I'm interested in performing chi-square test of group 1 x group2 (per gene/row) and group1 x group3 (per gene/row) and get the p-value and residuals in the same data frame. Creating columns for each comparison.

Genes<-c("GENE_A", "GENE_B","GENE_C")
Group1_Mut<-c(20,10,5)
Group1_WT<-c(40,50,55)
Group2_Mut<-c(10, 30, 10)
Group2_WT<-c(80, 60, 80)
Group3_Mut <- c(10,15,30)
Group3_WT <- c(30,40,45)
main<-data.frame(Genes,Group1_Mut,Group1_WT,Group2_Mut,Group2_WT, Group3_Mut,Group3_WT)

First I tried the example I found here at stackoverflow (but just for two groups comparations)

library(dplyr)

main %>%
 rowwise() %>%
 mutate(
  chisq.statistic = chisq.test(matrix(c(Group1_Mut, Group1_WT, Group2_Mut, Group2_WT), 
nrow = 2))$statistic
)

The chi-square value doesn´t match another statistics program

I tried again for just two groups:

main2 <- select(main,c(Group1_Mut, Group1_WT, Group2_Mut, Group2_WT))
main2 %>%
rowwise() %>%
mutate (statistics = chisq.test(main2))

but got this error:

Error: Problem with `mutate()` column `statistics`.
i `statistics = chisq.test(main2)`.
x `statistics` must be a vector, not a `htest` object.
i Did you mean: `statistics = list(chisq.test(main2))` ?
i The error occurred in row 1.

Then tried this:

 main2 %>%
    rowwise() %>%
    mutate (statistics = list(chisq.test(main2)))

got:

  Group1_Mut Group1_WT Group2_Mut Group2_WT statistics
       <dbl>     <dbl>      <dbl>     <dbl> <list>    
1         20        40         10        80 <htest>   
2         10        50         30        60 <htest>   
3          5        55         10        80 <htest>   

Any ideas on how can I do this test? Is there any functions that perform Chi-square on multiple comparisons?