Nothing
## ==========================================================================
## The filterSummary class provides a container for the output of summary
## on a filterResult
## ==========================================================================
## ==========================================================================
## Subsetting methods
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
## We need this to subset filterSummaries of multipleFilterResults
#' @export
setMethod("[[",
signature=signature(x="filterSummary",
i="numeric"),
definition=function(x, i, j, ...)
{
list(name=as.vector(x@name[i]), true=as.vector(x@true[i]),
false=as.vector(x@count[i]-x@true[i]),
count=x@count, p=as.vector(x@p[i]),
q=as.vector(1-x@p[i]))
})
## By name
#' @export
setMethod("[[",
signature=signature(x="filterSummary",
i="character"),
definition=function(x,i,j,...)
{
i <- which(i==names(x))
x[[i]]
})
## ==========================================================================
## This allows for a list-like accessor to the slots (and more...)
## Valid values are 'n', 'count', 'true', 'false', 'name', 'p' and 'q'
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#' @export
setMethod("$",
signature=signature(x="filterSummary"),
definition=function(x, name)
{
switch(name, "n"=x@count, "true"=x@true, "in"=x@true,
"false"=x@count-x@true, "out"=x@count-x@true,
"p"=x@p, "q"=1-x@p, "count"=x@count, "name"=x@name)
})
## ==========================================================================
## Return a more machine-readable output in form of a data.frame
## - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#' @importFrom BiocGenerics toTable
#' @export
setMethod("toTable",
signature=signature(x="filterSummary"),
definition=function(x, ...) {
data.frame(percent=x$p*100, count=x@count, true=x@true, false=x$false,
p=x$p, q=x$q)
})
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