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Gene counting for haplotype analysis

Source: R/genecounting.R
genecounting.Rd

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

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.

Details

Gene counting for haplotype analysis with missing data.

Note

adapted from GENECOUNTING.

References

Zhao JH, Lissarrague S, Essioux L, Sham PC (2002). “GENECOUNTING: haplotype analysis with missing genotypes.” Bioinformatics, 18(12), 1694-5. 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. 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. doi:10.1093/bioinformatics/bth071 .

See also

gc.em, LDkl

Author

Jing Hua Zhao

Examples

if (FALSE) { # \dontrun{
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
} # }