fusion: FUSION type 2 diabetes study

In fastR: Foundations and Applications of Statistics Using R

Description

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

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, data=fusion1m) 
xtabs(~t2d + Gdose, data=fusion1m) 
chisq.test( xtabs( ~t2d + genotype, data=fusion1m ) )
f1.glm <- glm( factor(t2d) ~ Gdose, data=fusion1m, family=binomial) 
summary(f1.glm)

fastR documentation built on May 1, 2019, 11:18 p.m.