Gene counting for haplotype analysis

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Description

Gene counting for haplotype analysis with missing data

Usage

1
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:

  1. 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.

  2. convll. set convergence criteria according to log-likelihood, if its value set to 1

  3. handle.miss. to handle missing data, if its value set to 1

  4. eps. the actual convergence criteria, with default value 1e-5

  5. tol. tolerance for genotype probabilities with default value 1e-8

  6. maxit. maximum number of iterations, with default value 50

  7. pl. criteria for trimming haplotypes according to posterior probabilities

  8. assignment. filename containing haplotype assignment

  9. 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 (h0^2)

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

Note

adapted from GENECOUNTING

Author(s)

Jing Hua Zhao

See Also

gc.em, LDkl

Examples

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## Not run: 
# 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)

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