SUM {AssotesteR} | R Documentation |
The SUM test has been proposed by Pan (2009) based on a modification of the Score. The idea behind the Sum Test is to test on only one parameter under the assumption of a common association strength between each of multiple genetic variants (e.g. SNPs) and the trait under analysis. The Sum test focuses on a scalar function of the multiple parameters with a resulting degree of freedom DF=1
SUM(y, X, perm = 100)
y |
numeric vector with phenotype status: 0=controls, 1=cases. No missing data allowed |
X |
numeric matrix or data frame with genotype data coded as 0, 1, 2. Missing data is allowed |
perm |
positive integer indicating the number of permutations (100 by default) |
There is no imputation for the missing data. Missing values are simply ignored in the computations.
An object of class "assoctest"
, basically a list with the following elements:
sum.stat |
sum statistic |
asym.pval |
asymptotic p-value |
perm.pval |
permuted p-value |
args |
descriptive information with number of controls, cases, variants, and permutations |
name |
name of the statistic |
Gaston Sanchez
Pan W (2009) Asymptotic tests of association with multiple SNPs in linkage disequilibrium. Genetic Epidemiology, 33: 497-507
Pan W, Han F, Shen X (2010) Test Selection with Application to Detecting Association with Multiple SNPs. Human Heredity, 69: 120-130
## Not run: # number of cases cases = 500 # number of controls controls = 500 # total (cases + controls) total = cases + controls # phenotype vector phenotype = c(rep(1, cases), rep(0, controls)) # genotype matrix with 10 variants (random data) set.seed(123) genotype = matrix(rbinom(total*10, 2, 0.05), nrow=total, ncol=10) # apply SUM with 500 permutations mysum = SUM(phenotype, genotype, perm=500) mysum ## End(Not run)