snp2bin: Transformation of SNPs to Binary Variables

Description

Transforms SNPs to binary variables.

Usage

snp2bin(mat, domrec = TRUE, refAA = FALSE, snp.in.col = TRUE, 
   monomorph = 0)

Arguments

mat

a matrix or data frame in which the genotypes of all SNPs are coded either by 0, 1 and 2, or by 1, 2 and 3, or by "AA", "AB" and "BB"

domrec

should each SNP be coded by two dummy variables from which one codes for
    a recessive, and the other for a dominant effect? If TRUE, then the first
    binary variable is set to 1 if the SNP is of the heterozygous or the homozygous varia

refAA

codes "AA" always for the homozygous reference gentoype? Only considered
   if the SNPs are coded by "AA", "AB" and "BB".
   If FALSE, it is evaluated SNPwise whether "AA" or

snp.in.col

does each column of mat correspond to a SNP (and each row to an observation)?
    If FALSE, it is assumed that each row represents a SNP, and each column an observation.

monomorph

a non-negative number. If a dummy variable contains monomorph or less
    values that differ from the more frequent value of this variable, then the variable is
    removed from the data set.

`Value`

A matrix containing the binary dummy variables.

`See Also`

recodeSNPs, recodeAffySNP

`Examples`

Run this code# Generate an example data set consisting of 10 rows (observations)
# and 5 columns (SNPs).

mat <- matrix(sample(3, 50, TRUE), 10)
colnames(mat) <- paste("SNP", 1:5, sep = "")

# Transform each SNP into two dummy variables, one that codes for
# a recessive effect and one that codes for a dominant effect.

snp2bin(mat)

# Transform each SNP into three dummy variables, where each of
# these variables codes for one of the three genotypes.

snp2bin(mat, domrec = FALSE)
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