Pheno | R Documentation |
Phenotype and genotype data from the Finland United States Investigation of NIDDM (type 2) Diabetes (FUSION) study.
Data frames with the following variables.
subject ID number for matching between data sets
a factor with levels case
control
body mass index
a factor with levels
F
M
age of subject at time phenotypes were colelcted
a factor with levels former
never
occasional
regular
total cholesterol
waist circumference (cm)
weight (kg)
height (cm)
waist hip ratio
systolic blood pressure
diastolic blood pressure
RS name of SNP
numeric ID for SNP
first allele coded as 1 = A, 2 = C, 3 = G, 4 = T
second allele coded as 1 = A, 2 = C, 3 = G, 4 = T
both alleles coded as a factor
number of A alleles
number of C alleles
number of G alleles
number of T alleles
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).
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)
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