lfspro {LFSPRO}R Documentation

Estimating TP53 mutation probability for families with Li-Fraumeni Syndrome

Description

We use Mendelian risk prediction model to estimate the probability for the counselee as a TP53 mutation carrier on the basis of his/her family cancer history.

Usage

lfspro(fam.data, cancer.data, penetrance.all, counselee.id, allef, nloci, mRate)

Arguments

fam.data

Family information data. See fam.data for details.

cancer.data

Cancer information data. See cancer.data for details.

penetrance.all

Penetrance data. See LFSpenet.2010 for details.

counselee.id

Data frame including two variables: fam.id (family id of counselees) and id (individual id of counselees).

allef

List. Allele frequency for each locus/gene. If there is only one gene and two alleles in the gene (allele frequency is 0.1 and 0.9), allef = list(c(0.1,0.9)), If there are two genes,two alleles (allele frequency is 0.1 and 0.9) for gene 1 and three alleles (allele frequncy is 0.2, 0.2 and 0.6) for gene 2, allef = list(c(0.1,0.9),c(0.2,0.2,0.6)). We suggeste to use list(c(1-maf,maf)). maf = 0.0001.

nloci

Number of loci/genes in the model. It is set to be 1 here.

mRate

Mutation rate. We suggest to use 5e-4.

Value

The TP53 mutation carrier probability for each counselee. It is a data frame with 3 variables: fam.id (family id), id (individual id) and pp(posterior probability that the counselee is a TP53 mutation carrier).

Author(s)

Gang Peng, Wenyi Wang

References

Peng, G., Bojadzieva, J., Ballinger, M., Thomas, D., Strong, L. and Wang, W. Estimating TP53 Mutation Carrier Probability in Families with Li-Fraumeni Syndrome Using LFSPRO. Submitted.

Chen, S., Wang, W., Broman, K. and Parmigiani, G. (2004) BayesMendel: An R Environment for Mendelian Risk Prediction. Statistical Application in Genetics and Molecular Biology, 3(1): Article 21.

See Also

LFSClassic, LFSChompret, lfsproC

Examples

allef.g <- list(c(0.9997,0.0003))
mRate.g <- 6e-05
options(stringsAsFactors = FALSE)
fam.id <- c("fam1","fam2","fam2","fam2","fam2")
id <- c(0,0,2,100,200)
counselee.id <- data.frame(fam.id, id)
lfspro(fam.data, cancer.data, LFSpenet.2010, counselee.id, allef.g, 1,mRate.g)

[Package LFSPRO version 1.0.5 Index]