R/population_annotate_functions.R

In MEP-LINCS/MEMA: Functions to preprocess and normalize MEMA data

#Functions to support MEMAs printed in 8 well plates
# 
# 
# #'Melt raw population dataset to combine wells
# #'
# #'\code{melt8Well} Converts a Tecan ArrayPro data file to a data.table with properly labeled columns.
# #'
# #'@param DT a data.table with columns of population intensity values in columns named by barcode, well, wavelength and data type(Raw/Net/Background)
# #'@param swap a logical on whether the data for the A and B rows should be swapped. This must be yes for 8 well data coming from the Array Pro software.
# #'@return A data.table in long format with columns of intensity readings for #' each data type and wavelength, barcode and well.
# #'@section Usage: This function reformats Array Pro results files that
# #' come from analyzing images from multiple channels, wells and plates.
# #' The column names are encoded as follows:
# #' Datatype is at the beginning of the column name as Raw, Net or
# #' Background. Barcode follows the curly brace symbol. Wavelength follows
# #'  the - symbol after the barcode. Well follows the - symbol after the
# #'  wavelength. The A and B well labels are swapped to align the Tecan
# #'  labeling to the actual well names.
# #'  @importFrom "data.table" ":="
# 
# #' @export
# melt8Well<-function(DT,swap = TRUE){
# 
#   intNames<-grep("Background|Net|Raw",colnames(DT), value = TRUE)
#   intNameType<-lapply(intNames,function(intName){
#     return(strsplit(intName,split=" ")[[1]][1])
#   })
#   intNameWL<-lapply(intNames,function(intName){
#     return(strsplit(intName,split="-")[[1]][2])
#   })
#   intNameWell<-lapply(intNames,function(intName){
#     return(strsplit(intName,split="-")[[1]][3])
#   })
#   intNameBarcode<-lapply(intNames,function(intName){
#     tmp<-strsplit(intName,split="[{]")[[1]][2]
#     return(strsplit(tmp,split="-")[[1]][1])
#   })
#   newIntNames<-make.names(paste(intNameType,intNameWL,intNameWell,intNameBarcode))
#   data.table::setnames(DT,colnames(DT[,intNames, with=FALSE]),newIntNames)
#   meltDT<-reshape2::melt(DT,measure=newIntNames,variable="TypeWLWellBarcode",value="Intensity", variable.factor=FALSE)
#   meltDT$Type<-unlist(lapply(meltDT$TypeWLWellBarcode,function(x){
#     return(strsplit(x,split="[.]")[[1]][1])
#   }))
#   meltDT$WL<-unlist(lapply(meltDT$TypeWLWellBarcode,function(x){
#     return(strsplit(x,split="[.]")[[1]][2])
#   }))
#   meltDT$Well<-unlist(lapply(meltDT$TypeWLWellBarcode,function(x){
#     well<-strsplit(x,split="[.]")[[1]][3]
#     wellChars<-strsplit(well,"")
#     Well<-paste0(wellChars[[1]][1],"0",wellChars[[1]][2])
#     return(Well)
#   }))
#   meltDT$Barcode<-unlist(lapply(meltDT$TypeWLWellBarcode,function(x){
#     return(strsplit(x,split="[.]")[[1]][4])
#   }))
#   meltDT[,TypeWLWellBarcode:=NULL]
#   meltDT$Type<-paste(meltDT$Type,meltDT$WL,sep=".")
#   #Delete the Wavelength only column
#   meltDT[,WL:=NULL]
#   data.table::setnames(meltDT,colnames(meltDT),make.names(colnames(meltDT)))
# 
#   #wide format creating columns of data organized by type and wavelength
#   DT<-reshape2::dcast(meltDT,...~Type,value.var="Intensity")
#   if (swap){
#     #Swap A and B well names to align Tecan labeling to the actual well names
#     DT$Well <- gsub("A","T",DT$Well)
#     DT$Well <- gsub("B","A",DT$Well)
#     DT$Well <- gsub("T","B",DT$Well)
#   }
# 
#   DT<-data.table::data.table(DT,key=c("Well","Barcode"))
#   return(DT)
# }