Description Usage Arguments Details Value Author(s) References See Also Examples
The WSS method has been proposed by Madsen and Browning (2009) as a pooling approach. In WSS, rare-variant counts within the same gene for each individual are accumulated rather than collapsing on them. Second, it introduces a weighting term to emphasize alleles with a low frequency in controls. Finally, the scores for all samples are ordered, and the WSS is computed as the sum of ranks for cases. The significance is determined by a permutation procedure.
1 | WSS(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:
wss.stat |
wss statistic |
perm.pval |
permuted p-value |
args |
descriptive information with number of controls, cases, variants, and permutations |
name |
name of the statistic |
Gaston Sanchez
Madsen BE, Browning SR (2009) A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic. PLoS Genetics, 5(2): e1000384
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ## 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 WSS with 500 permutations
mywss = WSS(phenotype, genotype, perm=500)
mywss
## End(Not run)
|
Loading required package: mvtnorm
WSS: Weighted Sum Statistic
Info:
cases controls variants n.perms
500 500 10 500
wss.stat perm.pval
247969.500 0.802
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