#' @name collapsData
#' @aliases collapsData,Rscexv-method
#' @rdname collapsData-methods
#' @docType methods
#' @description
#' @param dataObj TEXT MISSING
#' @param method TEXT MISSING default='median'
#' @title description of function collapsData
#' @export
setGeneric('collapsData', ## Name
function ( dataObj, method='median' ) {
standardGeneric('collapsData')
}
)
setMethod('collapsData', signature = c ('Tool_Plot'),
definition = function ( dataObj, method='median' ) {
ret <- matrix ( ncol= max(dataObj$clusters),nrow= ncol(data$z$PCR))
colnames(ret) <- paste('Cluster', 1:ncol(ret))
rownames(ret) <- colnames(dataObj$z$PCR)
for ( genecol in 1:nrow(ret) ) { ## genes
for ( cluster in 1:ncol(ret) ){
if ( method == 'median' ){
ret[genecol,cluster] = median(dataObj$z$PCR[which(dataObj$clusters == cluster),genecol ] )
}else if ( method == 'mean' ){
ret[genecol,cluster] = mean(dataObj$z$PCR[which(dataObj$clusters == cluster),genecol ] )
}else if ( method == 'var' ){
ret[genecol,cluster] = var(dataObj$z$PCR[which(dataObj$clusters == cluster),genecol ] )
}else if ( method == 'quantile70' ){
ret[genecol,cluster] = as.vector(quantile(dataObj$z$PCR[which(dataObj$clusters == cluster),genecol ],0.7 ))
}
else{
stop('method not implemented!')
}
}
}
if ( length( which(apply(ret,1,var) == 0))> 0 ){
ret <- ret[-which(apply(ret,1,var) == 0),]
}
ret
} )
#' @name collapsed_heatmaps
#' @aliases collapsed_heatmaps,Rscexv-method
#' @rdname collapsed_heatmaps-methods
#' @docType methods
#' @description
#' @param dataObj TEXT MISSING
#' @param what TEXT MISSING default='PCR'
#' @param functions TEXT MISSING default= c('median'
#' @param 'mean' TEXT MISSING
#' @param 'var' TEXT MISSING
#' @param 'quantile70') TEXT MISSING
#' @title description of function collapsed_heatmaps
#' @export
setGeneric('collapsed_heatmaps', ## Name
function ( dataObj, what='PCR', functions = c('median', 'mean', 'var', 'quantile70' ) ) {
standardGeneric('collapsed_heatmaps')
}
)
setMethod('collapsed_heatmaps', signature = c ('Tool_Plot'),
definition = function ( dataObj, what='PCR', functions = c('median', 'mean', 'var', 'quantile70' ) ) {
if ( ! is.vector(functions) ){
functions = c( functions )
}
data <- NULL
if ( what == 'PCR' ){
data = dataObj$z$PCR
}else if ( what =='FACS' ){
data = dataObj$FACS
}else {
stop('collapsed_heatmaps can only collaps PCR or FACS data' )
}
if ( !is.null(data)){
for( i in 1:length(functions)) {
reduced.filtered <- collapsData( data ,method=functions[i])
PCR.heatmap ( dataObj= list( data= reduced.filtered, genes= rownames(reduced.filtered)), ofile=paste(what,functions[i],sep="_") , margins=c(3,10),ColSideColors=rainbow(max(data$clusters)), Colv=F, Rowv=F, title=functions[i],RowSideColors=1)
}
}
} )
#' @name calc.ann
#' @aliases calc.ann,Rscexv-method
#' @rdname calc.ann-methods
#' @docType methods
#' @description
#' @param x TEXT MISSING
#' @param groups TEXT MISSING
#' @title description of function calc.ann
#' @export
setGeneric('calc.ann', ## Name
function (x, groups ) {
standardGeneric('calc.ann')
}
)
setMethod('calc.ann', signature = c ('Tool_Plot'),
definition = function (x, groups ) {
a <- min(TukeyHSD(aov(formula = as.vector(x) ~ as.factor(groups)))$"as.factor(groups)"[,4] )
if ( a < 1e-26 ) {
a = 1e-26
}
a
} )
#' @name get.GOI
#' @aliases get.GOI,Rscexv-method
#' @rdname get.GOI-methods
#' @docType methods
#' @description
#' @param ma TEXT MISSING
#' @param group TEXT MISSING
#' @param exclude TEXT MISSING default= NULL
#' @title description of function get.GOI
#' @export
setGeneric('get.GOI', ## Name
function ( ma, group, exclude = NULL ) {
standardGeneric('get.GOI')
}
)
setMethod('get.GOI', signature = c ('Tool_Plot'),
definition = function ( ma, group, exclude = NULL ) {
d <- apply( ma, 2, calc.ann, groups=group )
d <- d*ncol(ma) * max(group)
ret <- d[which(d< 0.05 )]
ret
} )
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