snpt.synthetic.gwas: Simulate synthetic genotypes

In lgl15/cnmtf: Prioritisation of single nucleotide variants using Corrected non-negative matrix tri-factorisation

Description

Function to create sythentic gwas dataset for a given snp type

Usage

snpt.synthetic.gwas(snpt, n.snps, n.pats = 2000, n.pops = 2,
  p.pops = c(0.5, 0.5), c.pops = c(0.6, 0.4), r.pops1 = c(1, 1),
  r.pops2 = c(3, 3), pl.pop1 = c(0.1, 0.1), pl.pop2 = c(0.15, 0.45),
  fst = 0.001)

Arguments

snpt	SNP type
n.snps	number of SNPs in the synthetic dataset
n.pats	number of patients in the synthetic dataset
n.pops	number of patient populations in the synthetic dataset
p.pops	proportion of patients in each population
c.pops	proportion of cases in each patient population
fst	Factor of differentiation between populations if allele.freq.model == "Balding-Nichols" .

Value

• db.g synthetic GWAS data set

• status disease status of the patient

• pop population ancestry of the patient

• snp.risk genotype relative risk for each SNP

Author(s)

Luis G. Leal, [e-mail]

See Also

Other Preprocessing functions: coding.scheme, construct.Vo, construct.Wu, create.network, degree.distribution, kernels.cnmtf, mapply.snpt.synthetic.gwas, rownet.hub

lgl15/cnmtf documentation built on May 28, 2019, 6:33 p.m.