genecounting: Gene counting for haplotype analysis

Description

Gene counting for haplotype analysis with missing data

Usage

genecounting(data,weight=NULL,loci=NULL,control=gc.control())

Arguments

data

genotype table

weight

a column of frequency weights

loci

an array containing number of alleles at each locus

control

is a function with the following arguments:

xdata. a flag indicating if the data involves X chromosome, if so, the first column of data indicates sex of each subject: 1=male, 2=female. The marker data are no different from the autosomal version for females, but for males, two copies of the single allele present at a given locus.
convll. set convergence criteria according to log-likelihood, if its value set to 1
handle.miss. to handle missing data, if its value set to 1
eps. the actual convergence criteria, with default value 1e-5
tol. tolerance for genotype probabilities with default value 1e-8
maxit. maximum number of iterations, with default value 50
pl. criteria for trimming haplotypes according to posterior probabilities
assignment. filename containing haplotype assignment
verbose. If TRUE, yields print out from the C routine

Value

The returned value is a list containing:

haplotype frequency estimates under linkage disequilibrium (LD)

haplotype frequency estimates under linkage equilibrium (no LD)

prob

genotype probability estimates

log-likelihood under linkage equilibrium

log-likelihood under linkage disequilibrium

hapid

unique haplotype identifier (defunct, see gc.em)

npusr

number of parameters according user-given alleles

npdat

number of parameters according to observed

htrtable

design matrix for haplotype trend regression (defunct, see gc.em)

iter

number of iterations used in gene counting

converge

a flag indicating convergence status of gene counting

di0

haplotype diversity under no LD, defined as $1 - \sum (h_{0}^{2})$

di1

haplotype diversity under LD, defined as $1 - \sum (h^{2}))$

resid

residuals in terms of frequency weights = o - e

References

Zhao, J. H., Lissarrague, S., Essioux, L. and P. C. Sham (2002). GENECOUNTING: haplotype analysis with missing genotypes. Bioinformatics 18(12):1694-1695

Zhao, J. H. and P. C. Sham (2003). Generic number systems and haplotype analysis. Comp Meth Prog Biomed 70: 1-9

Zhao, J. H. (2004). 2LD, GENECOUNTING and HAP: Computer programs for linkage disequilibrium analysis. Bioinformatics, 20, 1325-1326

Examples

Run this code

# NOT RUN {
require(gap.datasets)
# HLA data
data(hla)
hla.gc <- genecounting(hla[,3:8])
summary(hla.gc)
hla.gc$l0
hla.gc$l1

# ALDH2 data
data(aldh2)
control <- gc.control(handle.miss=1,assignment="ALDH2.out")
aldh2.gc <- genecounting(aldh2[,3:6],control=control)
summary(aldh2.gc)
aldh2.gc$l0
aldh2.gc$l1

# Chromosome X data
# assuming allelic data have been extracted in columns 3-13
# and column 3 is sex
filespec <- system.file("tests/genecounting/mao.dat")
mao2 <- read.table(filespec)
dat <- mao2[,3:13]
loci <- c(12,9,6,5,3)
contr <- gc.control(xdata=TRUE,handle.miss=1)
mao.gc <- genecounting(dat,loci=loci,control=contr)
mao.gc$npusr
mao.gc$npdat
# }

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