melanoma4CellLines.Rmd

---
title: "4 Cell Lines"
output: 
  html_document:
    toc: true
---

```{r setup, echo=FALSE, warning=FALSE, message=FALSE}
require("knitr")
opts_knit$set(root.dir="..")
opts_chunk$set(fig.align="center", fig.width=6, fig.height=6, dpi=300)
```

## Purpose
* Zeptosens analysis

## Setup 
```{r loadLibraries, message=FALSE, warning=FALSE}
library(xlsx)
library(zeptosensPkg)
```

## Normalization
```{r}
inputFile <- "inst/dataInst/R006_RFI_Export_Table.xls"
data06 <- readZeptosensXls(inputFile)

tmp <- data06[which(grepl("melanoma", data06[, "Sample.Name"], ignore.case=TRUE)),]

# Example Sample Name: S001_cell line_Melanoma_A2058 _DMSO_1hr_rep1

sampleNameEntries <- c("sampleNumber", NA, NA, "sample", "treatment", "time", "replicate")
array06 <- readZeptosensExport(tmp, sampleNameEntries)
write.table(array06, file="inst/dataInst/R006_RFI_Export_Int.txt", sep="\t", quote=FALSE, row.names=FALSE, col.names=TRUE)

replicateLabels <- unique(array06[,"replicate"])

array06[, c("sample", "treatment", "time", "antibody")]

#which(duplicated(array06[, c("sample", "treatment", "time", "antibody")]))

rep1 <- array06[which(array06$replicate == "rep1"), ]
idx1 <- with(rep1, order(sample, treatment, time, antibody))
rep1 <- rep1[idx1,]

rep2 <- array06[which(array06$replicate == "rep2"), ]
idx2 <- with(rep2, order(sample, treatment, time, antibody))
rep2 <- rep2[idx2,]

tmp <- cbind(rep1$readout, rep2$readout)
avgRepVals <- rowMeans(tmp)

sdVals <- apply(tmp, 1, sd)

avgRep <- rep1
avgRep[, "readout"] <- avgRepVals
avgRep[, "cv"] <- sdVals

write.table(avgRep,file="inst/dataInst/R006_RFI_Export_Avg.txt", sep="\t", quote=FALSE, row.names=FALSE, col.names=TRUE)
```

```{r normalization}
colClasses <- c("character","character","numeric")

tpl <- read.xlsx2("inst/dataInst/R006_TPL_Export_Table.xlsx", colClasses=colClasses, stringsAsFactors=FALSE, sheetIndex=1, endRow=65)
colnames(tpl) <- c("sampleNumber", "fullSampleName", "readout")

idx <- which(grepl("melanoma", tpl[, "fullSampleName"], ignore.case=TRUE))

splitNames <- splitSampleNames(tpl[idx, "fullSampleName"], sampleNameEntries)
tplSplit <- cbind(splitNames, tpl[idx,])

rep1 <- tplSplit[which(tplSplit$replicate == "rep1"), ]
idx1 <- with(rep1, order(sample, treatment, time))
rep1 <- rep1[idx1,]

rep2 <- tplSplit[which(tplSplit$replicate == "rep2"), ]
idx2 <- with(rep2, order(sample, treatment, time))
rep2 <- rep2[idx2,]

tmp <- cbind(rep1[, "readout"], rep2[, "readout"])
avgRepVals <- rowMeans(tmp)

sdVals <- apply(tmp, 1, sd)

avgRep <- rep1
avgRep[, "replicate"] <- rep("avg", nrow(avgRep))
avgRep[, "readout"] <- avgRepVals
avgRep[, "cv"] <- sdVals
```

```{r}
avgRepNames <- sapply(1:nrow(avgRep), function(i) {
    paste(avgRep[i, c("sample", "treatment", "time")], collapse="_")
})

array06Names <- sapply(1:nrow(array06), function(i) {
    paste(array06[i, c("sample", "treatment", "time")], collapse="_")
})

tmpArray06 <- cbind(tmpName=array06Names, array06)
tmpAvgRep <- cbind(tmpName=avgRepNames, avgRep)

normReadout <- NULL 

for(i in 1:nrow(tmpArray06)) {
    for(j in 1:nrow(tmpAvgRep)) {
        if(tmpArray06[i, "tmpName"] == tmpAvgRep[j, "tmpName"]) {
           normReadout <- c(normReadout, tmpArray06[i, "readout"] / tmpAvgRep[j, "readout"])
        }
    }
}

tmpArray06 <- cbind(tmpArray06, normReadout=normReadout)
```

## Normalization

* Data has a duplication in antibody AKT-Thr308 that needs resoultion
* Cell Sample Mix Sample Name needs correction

```{r}
tmp <- data06[which(grepl("mix", data06[, "Sample.Name"], ignore.case=TRUE)),]

normReadoutMix <- NULL

for(i in 1:nrow(tmpArray06)) {
    flag <- 0
    for(j in 1:nrow(tmp)) {
        if(tmpArray06[i, "antibody"] == tmp[j, "Analyte"]) {
           flag <- flag+1
           if(flag > 1) {
               cat("A: ", tmpArray06[i, "antibody"], " B: ", tmp[j, "Analyte"], flag, "\n")
           } else {
              normReadoutMix <- c(normReadoutMix, tmpArray06[i, "normReadout"] / tmp[j, "RFI"])
           }
        }
    }
}

tmpArray06 <- cbind(tmpArray06, normReadoutMix=normReadoutMix)
```

## 
```{r}
rep1 <- tmpArray06[which(tmpArray06$replicate == "rep1"), ]
idx1 <- with(rep1, order(sample, treatment, time, antibody))
rep1 <- rep1[idx1,]

rep2 <- tmpArray06[which(tmpArray06$replicate == "rep2"), ]
idx2 <- with(rep2, order(sample, treatment, time, antibody))
rep2 <- rep2[idx2,]

tmp <- cbind(rep1[, "readout"], rep2[, "readout"])
avgRepVals <- rowMeans(tmp)

sdVals <- apply(tmp, 1, sd)

avgRep <- rep1
avgRep[, "replicate"] <- rep("normAvg", nrow(avgRep))
avgRep[, "readout"] <- avgRepVals
avgRep[, "cv"] <- sdVals

# Remove tmpName column
avgRep <- avgRep[,!(names(avgRep) %in% c("tmpName"))]

write.table(avgRep, file="inst/dataInst/R006_RFI_Export_Int_Avg_Norm.txt", sep="\t", quote=FALSE, row.names=FALSE, col.names=TRUE)

for(sample in unique(avgRep[, "sample"])) {
    idx <- which(avgRep[, "sample"] == sample)
    write.table(avgRep[idx, ], file=file.path("inst/dataInst/", paste(sample, "R006_RFI_Export_Int_Avg_Norm.txt", sep="_")), sep="\t", quote=FALSE, row.names=FALSE, col.names=TRUE)
}
```

```{r, eval=FALSE}
tmp <- read.table("inst/dataInst/R006_RFI_Export_Int_Avg_Norm.txt", sep="\t", header=TRUE, stringsAsFactors=FALSE)
abMap <- read.table("inst/extdata/antibodyMap.txt", sep="\t", header=TRUE, stringsAsFactors=FALSE)

dataAb <- unique(tmp[,"antibody"])
abMap[, "ZeptosensLabel"]

setdiff(dataAb, abMap[, "ZeptosensLabel"])
```