BirchSPADE.save_original_data_with_clusters <- function(input_file_full
,outputs_dir
,clusters
,comp
,transforms
,remove_outliers
,rows_without_outliers) {
in_fcs <- SPADElike_transformFCS(SPADElike_readFCS(input_file_full, comp), transforms);
cells_data_og = exprs(in_fcs)
if (remove_outliers) {
cells_data_og = cells_data_og[rows_without_outliers,]
}
cells_data_og = cbind(cells_data_og, "cluster"=clusters)
params <- parameters(in_fcs)
pd <- pData(params)
# Add column named "cluster" to the FCS file
channel_number <- ncol(in_fcs)+1;
channel_id <- paste("$P",channel_number,sep="");
channel_name <- "cluster";
channel_range <- max(clusters)+1;
plist <- matrix(c(channel_name,channel_name,channel_range,0,channel_range-1));
rownames(plist) <- c("name","desc","range","minRange","maxRange");
colnames(plist) <- c(channel_id);
pd <- rbind(pd,t(plist))
pData(params) <- pd
# and save the file
out_frame <- flowFrame(cells_data_og, parameters = params, description=description(in_fcs))
input_file <- basename(input_file_full)
data_with_clusters_file = paste0(outputs_dir,"/",input_file,".cluster.fcs")
suppressWarnings(write.FCS(out_frame, data_with_clusters_file))
return(list("fcs_params" = parameters(in_fcs)@data, "file" = data_with_clusters_file))
}
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