RFGLS (version 1.1)

pheno: Simulated quantitative-trait dataset

Description

A dataset of observations on a normally distributed phenotype, generated with means conditional on genotype at the effect locus. All six family-types recognized in package RFGLS are represented.

Usage

data(pheno)

Format

A data frame with 4050 observations on the following 6 variables:

FAMID

"Family ID." Each family in the dataset is uniquely identified by a value of FAMID, which are all multiples of 10.

ID

Individual ID. Each subject in the dataset is uniquely identified by a value of ID, which is equal to his/her INDIV plus his/her FAMID.

FTYPE

"Family-type." RFGLS recognizes six different family-types, five of which are, at largest, four-person nuclear families (two parents, two offspring), distinguished by how the two offspring are related to one another:

1. MZ-twin families,
2. DZ-twin families,
3. Adoptive-offspring families,
4. Non-twin bio-offspring families,
5. "Mixed" families with one bio and one adopted offspring, and
6. "Independent observations," who do not fit into a four-person nuclear family.

INDIV

"Individual code," which represents how a subject fits into his/her family: INDIV=1 is for "Offspring #1," INDIV=2 is for "Offspring 2," INDIV=3 is for the mother, and INDIV=4 is for the father. In families of FTYPE=5, the biological offspring has INDIV=1, and the adopted offspring, INDIV=2. All "independent observations" (i.e., FTYPE=6) have INDIV=1. Note that individuals in a given family are ordered by their INDIV.

Zscore

The phenotype score.

IsFemale

Binary indicator; a value of 1 indicates female sex. All offspring in families of type #2 (DZ twins) happen to be same-sex, but this is not a requirement.

Details

Each family's phenotype scores were generated from a multivariate normal distribution (mvrnorm in package mvtnorm) with a centroid defined conditional upon the family members' genotypes on the effect locus (rs7681769 in dataset geno), and a variance matrix with 1s on its diagonal and covariances (really, correlations) consistent with an additive heritability of 0.5 and a shared-environmentality of 0.2, but zero assortative mating.

Examples

data(pheno)
str(pheno)
qqnorm(pheno$Zscore[pheno$INDIV==1]) ##<--Normally distributed phenotype.
qqline(pheno$Zscore[pheno$INDIV==1])
##Also see examples for functions fgls(), gls.batch(), and gls.batch.get().