#' @name interesting_genes
#' @aliases interesting_genes,SingleCellsNGS-method
#' @rdname interesting_genes-methods
#' @docType methods
#' @description This method uses the values created by update.measurements() and selects the most interesting subset of genes.
#' @param x the SingleCellsNGS object
#' @param Min the minimal fraction of cells expresing the gene default=0.4
#' @param Max the maximal fraction of cells expresing the gene default=0.8
#' @param genes how many genes you want to get back default=100
#' @title description of function interesting_genes
#' @export
setGeneric('interesting_genes', ## Name
function (x, Min=0.4, Max=0.8 , genes=100) { ## Argumente der generischen Funktion
standardGeneric('interesting_genes') ## der Aufruf von standardGeneric sorgt für das Dispatching
}
)
setMethod('interesting_genes', signature = c ('SingleCellsNGS'),
definition = function (x, Min=0.4, Max=0.8 , genes=100) {
if ( is.null(x@annotation$mean_var) ) {
x <- update.measurements ( x )
}
possible <- which( x@annotation$fraction_expressing > Min & x@annotation$fraction_expressing < Max )
order.possible <- order(x@annotation$mean_var[possible])
rownames(x@data)[possible[order.possible][1:genes]]
}
)
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