# drggn.gm: causal models with G*G In IFP: Identifying Functional Polymorphisms

## Description

provides concordance probabilities of relative pairs for a causal model with G*G component

## Usage

 `1` ``` drggn(fd,fr) ```

## Arguments

 `fd` an array (size=number of dominant genes+recessive genes) of dominant gene frequencies including 0 values of recessive genes of G*G component `fr` an array (size=number of dominant genes+recessive genes) of recessive gene frequencies including 0 values of dominant genes of G*G component

## Value

a list of PLI and a 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)

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```### PLI=0.01. ppt<-0.01 ### g*g model pp<-ppt # the proportion of G*G component in total populations gd<-sqrt(pp) # dominant gene proportion = recessive gene proportion fd<-array(1-sqrt(1-gd^(1/2)),2) # two dominant genes tt<-2 # the number of recessive genes: 2 temp<-(pp/gd)^(1/2/tt) fr<-c(array(0,length(fd)),array(temp,tt)) fd<-c(fd,array(0,tt)) drggn(fd,fr) ```