Nothing
#'ORWSS: Odds Ratio Weighted Sum Statistic
#'
#'The ORWSS method has been proposed by Feng et al (2011) and it is based on a
#'weighted sum statistic like the WSS method of Madsen and Browning (2009).
#'ORWSS uses the logarithm of the odds ratio of a genetic variant as the weight
#'for that variant, rather than the variance estimated in controls.
#'
#'When \code{c.param=NULL}, the weights of the sum statistic are simply the
#'logarithm of the amended Odds Ratio of each variant (as in Dai et al 2012).
#'Alternative values like \code{c.param=1.64} or \code{c.param=1.28} are
#'suggested in Feng et al (2011). \cr
#'
#'There is no imputation for the missing data. Missing values are simply
#'ignored in the computations.
#'
#'@param y numeric vector with phenotype status: 0=controls, 1=cases. No
#'missing data allowed
#'@param X numeric matrix or data frame with genotype data coded as 0, 1, 2.
#'Missing data is allowed
#'@param c.param optional value to specify the \code{c} parameter. See
#'reference Feng et al, 2011
#'@param perm positive integer indicating the number of permutations (100 by
#'default)
#'@return An object of class \code{"assoctest"}, basically a list with the
#'following elements:
#'@returnItem orwss.stat orwss statistic
#'@returnItem perm.pval permuted p-value
#'@returnItem args descriptive information with number of controls, cases,
#'variants, and permutations
#'@returnItem name name of the statistic
#'@author Gaston Sanchez
#'@seealso \code{\link{WSS}}
#'@references Feng T, Elston RC, Zhu X (2011) Detecting Rare and Common
#'Variants for Complex Traits: Sibpair and Odds Ratio Weighted Sum Statistics
#'(SPWSS, ORWSS). \emph{Genetic Epidemiology}, \bold{35}: 398-409 \cr
#'
#'Dai Y, Jiang R, Dong J (2012) Weighted selective collapsing strategy for
#'detecting rare and common variants in genetic association study. \emph{BMC
#'Genetics}, \bold{13}:7
#'@examples
#'
#' \dontrun{
#'
#' # 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 ORWSS with c.param=NULL and 500 permutations
#' myorwss1 = ORWSS(phenotype, genotype, c.param=NULL, perm=100)
#' myorwss1
#'
#' # apply ORWSS with c.param=1.64 (see Feng et al 2011)
#' myorwss2 = ORWSS(phenotype, genotype, c.param=1.64, perm=100)
#' myorwss2
#' }
#'
ORWSS <-
function(y, X, c.param=NULL, perm=100)
{
## checking arguments
Xy_perm = my_check(y, X, perm)
y = Xy_perm$y
X = Xy_perm$X
perm = Xy_perm$perm
if (!is.null(c.param))
{
if (mode(c.param)!= "numeric" || length(c.param) != 1
|| c.param<0 || c.param>=10)
stop("argument 'c.param' incorreclty defined; must be a non-negative value")
}
Xnew = X
Xnew[Xnew!=0] = 1
## running orwss method
orwss.stat = my_orwss_method(y, Xnew, c.param)
## permutations
perm.pval = NA
if (perm > 0)
{
x.perm = rep(0, perm)
for (i in 1:perm)
{
perm.sample = sample(1:length(y))
x.perm[i] = my_orwss_method(y[perm.sample], Xnew, c.param)
}
## p-value
perm.pval = sum(x.perm > orwss.stat) / perm
}
## results
name = "ORWSS: Odds Ratio Weighted Sum Statistic"
arg.spec = c(sum(y), length(y)-sum(y), ncol(X), perm)
names(arg.spec) = c("cases", "controls", "variants", "n.perms")
res = list(orwss.stat = orwss.stat,
perm.pval = perm.pval,
args = arg.spec,
name = name)
class(res) = "assoctest"
return(res)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.