Here is a working snippet.

library(epitools)
mat <- matrix(c(10,15,60,25,98, 12,10,70,28,14, 9,11,68,10,12 ,8,13,20,11,58) ,ncol=2)
colnames(mat) <- c("treatmentA","treatmentB")
row.names(mat) <- paste("Cond",rep(1:10,1))
dimnames(mat) <- list("Condition" = row.names(mat), "instrument" = colnames(mat))

> mat
         instrument
Condition treatmentA treatmentB
  Cond 1          10          9
  Cond 2          15         11
  Cond 3          60         68
  Cond 4          25         10
  Cond 5          98         12
  Cond 6          12          8
  Cond 7          10         13
  Cond 8          70         20
  Cond 9          28         11
  Cond 10         14         13

# I'm not sure how to use the rev option of the oddsration works here. I'm trying to see if any of the treatments has an effect on each condition, so for example if treatment A has an effect on cond1 compared to treatmentB. And so on for each condition.
I also don't understand why i get an NA value  on cond10 ???

> oddsratio(mat,rev="r") . Shoudl this be rev="r" or rev="c"
$data
         instrument
Condition treatmentA treatmentB Total
  Cond 10         14         58    72
  Cond 9          28         11    39
  Cond 8          70         20    90
  Cond 7          10         13    23
  Cond 6          12          8    20
  Cond 5          98         12   110
  Cond 4          25         10    35
  Cond 3          60         68   128
  Cond 2          15         11    26
  Cond 1          10          9    19
  Total          342        220   562

$measure
         odds ratio with 95% C.I.
Condition   estimate      lower      upper
  Cond 10 1.00000000         NA         NA
  Cond 9  0.09829116 0.03774410 0.23797549
  Cond 8  0.07099961 0.03179722 0.14918984
  Cond 7  0.31836593 0.11348206 0.89217010
  Cond 6  0.16616586 0.05412347 0.48011838
  Cond 5  0.03081892 0.01269306 0.06870094
  Cond 4  0.10021240 0.03728880 0.24932078
  Cond 3  0.27705710 0.13577945 0.53625865
  Cond 2  0.18189409 0.06613614 0.47770002
  Cond 1  0.22261481 0.07313306 0.65711936

$p.value
         two-sided
Condition   midp.exact fisher.exact   chi.square
  Cond 10           NA           NA           NA
  Cond 9  8.154112e-08 1.049524e-07 5.662609e-08
  Cond 8  5.306866e-14 6.524468e-14 1.539341e-13
  Cond 7  2.978326e-02 2.860464e-02 2.092707e-02
  Cond 6  8.811686e-04 1.259777e-03 3.660559e-04
  Cond 5  0.000000e+00 3.867056e-22 3.600564e-21
  Cond 4  2.707171e-07 3.071608e-07 1.590623e-07
  Cond 3  9.355292e-05 1.212804e-04 1.149120e-04
  Cond 2  5.085059e-04 7.732183e-04 2.499965e-04
  Cond 1  6.702975e-03 6.992229e-03 3.499738e-03

$correction
[1] FALSE

attr(,"method")
[1] "median-unbiased estimate & mid-p exact CI"
>

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