| genecounting {gap} | R Documentation |
Gene counting for haplotype analysis with missing data
genecounting(data, weight = NULL, loci = NULL, control = gc.control())
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:
|
The returned value is a list containing:
haplotype frequency estimates under linkage disequilibrium (LD)
haplotype frequency estimates under linkage equilibrium (no LD)
genotype probability estimates
log-likelihood under linkage equilibrium
log-likelihood under linkage disequilibrium
unique haplotype identifier (defunct, see gc.em)
number of parameters according user-given alleles
number of parameters according to observed
design matrix for haplotype trend regression (defunct, see gc.em)
number of iterations used in gene counting
a flag indicating convergence status of gene counting
haplotype diversity under no LD, defined as 1-sum (h0^2)
haplotype diversity under LD, defined as 1-sum (h^2)
residuals in terms of frequency weights = o - e
adapted from GENECOUNTING.
Jing Hua Zhao
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
## 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)