Learn R Programming

gap (version 1.1-20)

comp.score: score statistics for testing genetic linkage of quantitative trait

Description

The function empirically estimate the variance of the score functions. The variance-covariance matrix consists of two parts: the additive part and the part for the individual-specific environmental effect. Other reasonable decompositions are possible.

This program has the following improvement over "score.r":

1. It works with selected nuclear families

2. Trait data on parents (one parent or two parents), if available, are utilized.

3. Besides a statistic assuming no locus-specific dominance effect, it also computes a statistic that allows for such effect. It computes two statistics instead of one.

Function "merge" is used to merge the IBD data for a pair with the transformed trait data (i.e., \(w_kw_l\)).

Usage

comp.score(ibddata="ibd_dist.out", phenotype="pheno.dat", mean=0,
                  var=1, h2=0.3)

Arguments

ibddata

The output file from GENEHUNTER using command "dump ibd". The default file name is \(ibd_dist.out\).

phenotype

The file of pedigree structure and trait value. The default file name is "pheno.dat". Columns (no headings) are: family ID, person ID, father ID, mother ID, gender, trait value, where Family ID and person ID must be numbers, not characters. Use character "NA" for missing phenotypes.

mean

(population) mean of the trait, with a default value of 0

var

(population) variance of the trait, with a default value of 1

h2

heritability of the trait, with a default value of 0.3

Value

a matrix with each row containing the location and the statistics and their p-values.

References

Kruglyak L, Daly MJ, Reeve-Daly MP, Lander ES (1996) Parametric and Nonparametric linkage analysis: a unified multipoint approach. Am J Hum Genet 58:1347-1363

Kruglyak L, Lander ES (1998) Faster multipoint linkage analysis using Fourier transforms J Comp Bio 1998 5:1-7

Wang K (2005) A likelihood approach for quantitative-trait-locus mapping with selected pedigrees. Biometrics 61:465-473

Examples

Run this code
# NOT RUN {
# An example based on GENEHUNTER version 2.1, with quantitative trait data in file
# "pheno.dat" generated from the  standard normal distribution. The following
# exmaple shows that it is possible to automatically call GENEHUNTER using R
# function "system".

cwd <- getwd()
cs.dir <- file.path(path.package("gap"),"tests/comp.score")
setwd(cs.dir)
dir()
# system("gh < gh.inp")
cs.default <- comp.score()
setwd(cwd)
# }

Run the code above in your browser using DataLab