You can calculate the relative risk as  (pos1/total1)/(pos2/total2) 
here, pos1 is the samples in the first group, 
pos2 in the second group.
Use the epitab function of the epitools package:
##   install.packages("epitools")
library("epitools")
After installing, try this:
tab <- matrix(c(4,16,40,168),byrow=TRUE,nrow=2)
epitab(tab,method="riskratio")
## $tab
##           Outcome
## Predictor  Disease1        p0 Disease2        p1 riskratio     lower    upper
##   Exposed1        4 0.2000000       16 0.8000000  1.000000        NA       NA
##   Exposed2       40 0.1923077      168 0.8076923  1.009615 0.8030206 1.269361
##           Outcome
## Predictor  p.value
##   Exposed1      NA
##   Exposed2       1
I hope this helped.