itegeppXXR: Haplotype estimation routine for single individual data

In HapEstXXR: Multi-Locus Stepwise Regression

Description

itegeppXXR is haplotype estimation routine for samples of independent individual genotypes (EM-algorithm).

Usage

itegeppXXR(geno, des = 0, lim = 0.05)

Arguments

geno	(n,m)-Matrix; n=No of Individuals, m=No of SNPs; R-Code: 1-column genotype matrix - code 1 = 1/1, 3 = 1/2, 2 = 2/2
des	des=1 haplotype pairs, des=0 single haplotypes
lim	Threshold for combining rare haplotypes

Details

Inferring haplotypes by EM-Algorithm

Value

hap.id	Id. of haplotypes
hap	estimated haplotypes
freq	haplotype frequencies
hapres	individual haplotypes
likres	Likelihood value
desres	Design matrix for the model (des=1 => Haplotype pairs, des=0 => single haplotypes)

Note

This function works only up to 15 SNP haplotypes

Author(s)

Sven Knueppel and Klaus Rohde

References

Excoffier L, Slatkin M (1995) Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol 12:921-927

Examples

  set.seed(123456)
  ns <- 4  # Number of SNPs
  N <- 2000   # Number of individuals
  patid <- N:1
  geno <- matrix(sample(c(1, 2, 3), ns * N, replace = TRUE), ncol = ns)
  iteHAP <- itegeppXXR(geno, des = 1, lim = 0.01)

Example output

Loading required package: survival

HapEstXXR documentation built on May 1, 2019, 10:54 p.m.