Description Usage Arguments Value Note Author(s) See Also Examples
View source: R/AddAffectedToTree.R
A function that takes a tree and adds affection status using user given cancer types and penetrances.
1 | AddAffectedToTree(tree.f, frequencies.df = NULL, g = 4, benign.boolean=FALSE)
|
tree.f |
Output from |
frequencies.df |
A dataframe giving the penetrance of the desired affection. For convenience this can be one of the included penetrance data frames ( |
g |
A parameter giving the generation to select a proband in. |
benign.boolean |
A boolean variable which tells the program to simulate disease status for a benign variant when benign.boolean is TRUE. |
Adds the affection status the inputted tree. The added columns are based on the inputted frequencies.df. For the default BRCA1Frequencies.df the extra columns are listed below.
famid |
An integer id for the current tree. This is only useful for multiple trees. |
bBRCA1.d |
A boolean/integer depicting whether the individual has breast cancer(1) or not(0). |
oBRCA1.d |
A boolean/integer depicting whether the individual has ovarian cancer(1) or not(0) |
bBRCA1.aoo |
An integer giving the age of onset of the breast cancer if the individual is affected or NA if not. |
oBRCA1.aoo |
An integer giving the age of onset of the ovarian cancer if the individual is affected or NA if not. |
proband |
A boolean/integer labeling the proband(one with the variant and the disease) with a 1 and everyone else with 0. Note that if no suitable proband is found, all members will receive a -1. |
Note that CRAN throws up a note when this package is checked saying "no visible binding for global variable...". This is normal and does not affect the analysis.
John Michael O. Ranola and Brian H. Shirts
See also MakeTree
, MakeAffectedTrees
, and PlotPedigree
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | ## Not run:
#summaries of all the data
str(BRCA1Frequencies.df)
str(BRCA2Frequencies.df)
str(MLH1Frequencies.df)
str(USDemographics.df)
str(ChinaDemographics.df)
#Make a tree with no affection status, g=4 generations above, gdown=2 generations below,
#seed.age=50, and demographics.df=NULL which defaults to USDemographics.df.
tree1=MakeTree()
#Make a tree using Chinese demographics instead.
tree2=MakeTree(demographics.df=ChinaDemographics.df)
#Add affection statust to tree2 using BRCA1Frequencies.df which gives the BRCA1
#penetrance function
tree1a=AddAffectedToTree(tree.f=tree1,frequencies.df=BRCA1Frequencies.df)
#make a tree with affection status (same as running MakeTree() and then AddAffectedToTree())
tree3=MakeAffectedTrees(n=1,g=2,gdown=2,frequencies.df=MLH1Frequencies.df)
#tree4=MakeAffectedTrees(n=1,g=2,gdown=2,frequencies.df=BRCA2Frequencies.df)
#Depending on the size of the pedigree generated, probands (defined here as members of the
#pedigree who are carriers of the genotype with the disease) may not always be present in
#the pedigree. To alleviate this problem in this example we manually generate a pedigree.
#Note that this is from the Mohammadi paper where the Likelihood method originates from.
ped=data.frame(degree=c(3,2,2,3,3,1,1,2,2,3), momid=c(3,NA,7,3,3,NA,NA,7,NA,8),
dadid=c(2,NA,6,2,2,NA,NA,6,NA,9), id=1:10, age=c(45,60,50,31,41,68,65,55,62,43),
female=c(1,0,1,0,1,0,1,1,0,1), y.born=0, dead=0, geno=2, famid=1, bBRCA1.d=0, oBRCA1.d=0,
bBRCA1.aoo=NA, oBRCA1.aoo=NA, proband=0)
ped$y.born=2010-ped$age
ped$geno[c(1,3)]=1
ped$bBRCA1.d[c(1,3)]=1
ped$bBRCA1.aoo[1]=45
ped$bBRCA1.aoo[3]=50
ped$proband[1]=1
ped=ped[c(6,7,2,3,8,9,1,4,5,10),]
#Calculate the likelihood ratio
CalculateLikelihoodRatio(ped=ped, affected.vector={ped$bBRCA1.d|ped$oBRCA1.d}, gene="BRCA1")
#Plot the pedigree
PlotPedigree(ped, affected.vector={ped$bBRCA1.d|ped$oBRCA1.d})
#Rank and plot the members of the pedigree with unknown genotypes
RankMembers(ped=ped, affected.vector={ped$bBRCA1.d|ped$oBRCA1.d}, gene="BRCA1")
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.