fusion: FUSION type 2 diabetes study

In fastR: Data sets and utilities for Foundations and Applications of Statistics by R Pruim

Description

Phenotype and genotype data from the Finland United States Investigation of NIDDM (type 2) Diabetes (FUSION) study.

Usage

data(pheno); data(fusion1); data(fusion2)

Format

Data frames with the following variables.

id

subject ID number for matching between data sets

t2d

a factor with levels case control

bmi

body mass index

sex

a factor with levels F M

age

age of subject at time phenotypes were colelcted

smoker

a factor with levels former never occasional regular

chol

total cholesterol

waist

waist circumference (cm)

weight

weight (kg)

height

height (cm)

whr

waist hip ratio

sbp

systolic blood pressure

dbp

diastolic blood pressure

marker

RS name of SNP

markerID

numeric ID for SNP

allele1

first allele coded as 1=A, 2=C, 3=G, 4=T

allele2

second allele coded as 1=A, 2=C, 3=G, 4=T

genotype

both alleles coded as a factor

Adose

number of A alleles

Cdose

number of C alleles

Gdose

number of G alleles

Tdose

number of T alleles

Source

Similar to the data presented in

Laura J. Scott, Karen L. Mohlke, Lori L. Bonnycastle, Cristen J. Willer, Yun Li, William L. Duren, Michael R. Erdos, Heather M. Stringham, Pe- ter S. Chines, Anne U. Jackson, Ludmila Prokunina-Olsson, Chia-Jen J. Ding, Amy J. Swift, Narisu Narisu, Tianle Hu, Randall Pruim, Rui Xiao, Xiao- Yi Y. Li, Karen N. Conneely, Nancy L. Riebow, Andrew G. Sprau, Maurine Tong, Peggy P. White, Kurt N. Hetrick, Michael W. Barnhart, Craig W. Bark, Janet L. Goldstein, Lee Watkins, Fang Xiang, Jouko Saramies, Thomas A. Buchanan, Richard M. Watanabe, Timo T. Valle, Leena Kinnunen, Goncalo R. Abecasis, Elizabeth W. Pugh, Kimberly F. Doheny, Richard N. Bergman, Jaakko Tuomilehto, Francis S. Collins, and Michael Boehnke, A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility vari- ants, Science (2007).

Examples

data(pheno); data(fusion1); data(fusion2)
fusion1m <- merge(fusion1, pheno, by="id", all.x=FALSE, all.y=FALSE) 
xtabs(~t2d + genotype, fusion1m) 
xtabs(~t2d + Gdose, fusion1m) 
chisq.test( xtabs( ~t2d + genotype, fusion1m ) )
f1.glm <- glm( factor(t2d) ~ Gdose, fusion1m, family=binomial) 
summary(f1.glm)

fastR documentation built on May 2, 2019, 5:53 p.m.