# causal models with all possible causal factors: G, G*G, G*E and E provides concordance probabilities of relative pairs for a causal model with G, G*G, G*E and E components ```r drgegggne(fdg,frg,fdgg,frgg,fdge,frge,eg,e) ``` ## Arguments - `fdg`: an array (size=number of dominant genes+recessive genes) of dominant gene frequencies including 0 values of recessive genes of G component - `frg`: an array (size=number of dominant genes+recessive genes) of recessive gene frequencies including 0 values of dominant genes of G component - `fdgg`: an array (size=number of dominant genes+recessive genes) of dominant gene frequencies including 0 values of recessive genes of G*G component - `frgg`: an array (size=number of dominant genes+recessive genes) of recessive gene frequencies including 0 values of dominant genes of G*G component - `fdge`: an array (size=number of dominant genes+recessive genes) of dominant gene frequencies including 0 values of recessive genes of G*E component - `frge`: an array (size=number of dominant genes+recessive genes) of recessive gene frequencies including 0 values of dominant genes of G*E component - `eg`: a proportion of population who are exposed to environmental cause of G*E interactiong the genetic cause of G*E during their entire life - `e`: a proportion of population who are exposed to environmental cause during their entire life ## Returns matrix of NN, ND, and DD probabilities of 9 relative pairs: 1:mzt,2:parent-offspring,3:dzt,4:sibling,5:2-direct(grandparent-grandchild),6:3rd(uncle-niece),7:3-direct(great-grandparent-great-grandchild),8:4th (causin),9:4d(great-great-grandparent-great-great-grandchild) ## See Also drggn drgegne ## Examples ```r ### PLI=0.01. ppt<-0.01 ### for a model without one or more missing causal factors, ### set the relevant parameters as zero. pg<-0.002 # the proportion of G component in total populations pgg<-0.002 # the proportion of G*G component in total populations pge<-0.003 # the proportion of G*E component in total populations e<-1-(1-ppt)/(1-pg)/(1-pgg)/(1-pge) # the proportion of E component in total populations fd<-0.001 # one dominant gene tt<-3 # the number of recessive genes temp<-sqrt(1-((1-pg)/(1-fd)^2)^(1/tt)) fr<-c(array(0,length(fd)),array(temp,tt)) fd<-c(fd,array(0,tt)) ppd<-sqrt(pgg) fdg<-array(1-sqrt(1-ppd^(1/2)),2) ttg<-1 temp<-(pgg/ppd)^(1/2/ttg) frg<-c(array(0,length(fdg)),array(temp,ttg)) fdg<-c(fdg,array(0,ttg)) ppe<-0.5 ppg<-pge/ppe fdge<-0.002 ttge<-2 # the number of recessive genes temp<-sqrt(1-((1-ppg)/(1-fdge)^2)^(1/ttge)) frge<-c(array(0,length(fdge)),array(temp,ttge)) fdge<-c(fdge,array(0,ttge)) drgegggne(fd,fr,fdg,frg,fdge,frge,ppe,e) ```

drgegggne.gm function