genecounting {gap}

Gene counting for haplotype analysis

Description

Gene counting for haplotype analysis

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

Details

Gene counting for haplotype analysis with missing data.

Value

The returned value is a list containing:

• h haplotype frequency estimates under linkage disequilibrium (LD).

• h0 haplotype frequency estimates under linkage equilibrium (no LD).

• prob genotype probability estimates.

• l0 log-likelihood under linkage equilibrium.

• l1 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.

Note

adapted from GENECOUNTING.

Author(s)

Jing Hua Zhao

References

Zhao JH, Lissarrague S, Essioux L, Sham PC (2002). “GENECOUNTING: haplotype analysis with missing genotypes.” Bioinformatics, 18(12), 1694-5. ISSN 1367-4803 (Print) 1367-4803, doi:10.1093/bioinformatics/18.12.1694.

Zhao JH, Sham PC (2003). “Generic number systems and haplotype analysis.” Comput Methods Programs Biomed, 70(1), 1-9. ISSN 0169-2607 (Print) 0169-2607, doi:10.1016/s0169-2607(01)00193-6.

Zhao JH (2004). “2LD. GENECOUNTING and HAP: computer programs for linkage disequilibrium analysis.” Bioinformatics, 20(8), 1325-6. ISSN 1367-4803 (Print) 1367-4803, doi:10.1093/bioinformatics/bth071.

See Also

gc.em, LDkl

Examples

## 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

## End(Not run)