processDemultiplex <- function(demuxStatsXML){
if(file.exists(demuxStatsXML)){
demuxStatsXMLparse <- xmlTreeParse(demuxStatsXML)
demuxStatsXML_root <- xmlRoot(demuxStatsXMLparse)
Projects <- demuxStatsXML_root[[1]]
flowcellID <- xmlAttrs(Projects)
Projects_Info <- list()
for(p in seq_along(Projects)){
Project <- Projects[[p]]
Project_Name <- xmlAttrs(Project)
Project_Sample_Info <- list()
for(s in seq_along(Project)){
Sample <- Project[[s]]
Sample_Name <- xmlAttrs(Sample)
Sample_BarcodeExpected <- Sample[[1]]
Sample_BarcodeExpected_Name <- xmlAttrs(Sample[[1]])
Project_Sample_BarcodeExpected_Lane_Info <- list()
for(b in seq_along(Sample_BarcodeExpected)){
Lane <- Sample_BarcodeExpected[[b]]
Lane_Name <- xmlAttrs(Lane)
Lane_BarcodeCount <- as.integer(xmlValue(Lane[["BarcodeCount"]]))
Lane_PerfectBarcodeCount <- as.integer(xmlValue(Lane[["PerfectBarcodeCount"]]))
Project_Sample_BarcodeExpected_Lane_Info[[b]] <- data.frame(BarcodeCount = Lane_BarcodeCount,
PerfectBarcodeCount = Lane_PerfectBarcodeCount)
names(Project_Sample_BarcodeExpected_Lane_Info)[b] <- paste0("Lane",xmlAttrs(Lane))
}
psbeliMat <- sapply(Project_Sample_BarcodeExpected_Lane_Info,function(x)x)
psbeliMatDF <- data.frame(BarcodeStat=rownames(psbeliMat),psbeliMat)
psbeliMatDF <- tidyr::gather(psbeliMatDF,Lane,Count,-BarcodeStat)
Project_Sample_Info[[s]] <- data.frame(Barcode = rep(Sample_BarcodeExpected_Name,nrow(psbeliMatDF)),
psbeliMatDF)
names(Project_Sample_Info)[s] <- Sample_Name
}
psiMat <- do.call(rbind,Project_Sample_Info)
psiMatDF <- data.frame(Sample=gsub("\\..*","",rownames(psiMat)),psiMat)
Projects_Info[[p]] <- data.frame(Project = rep(Project_Name,nrow(psiMat)),
psiMatDF)
names(Projects_Info)[p] <- Project_Name
}
Projects_DF2 <- do.call(rbind,Projects_Info)
rownames(Projects_DF2) <- NULL
return(Projects_DF2)
}
return(NULL)
}
processConvStats <- function(ConvStatsXML){
if(file.exists(ConvStatsXML)){
convStatsXMLparse <- xmlTreeParse(ConvStatsXML)
convStatsXML_root <- xmlRoot(convStatsXMLparse)
Projects <- convStatsXML_root[[1]]
flowcellID <- xmlAttrs(Projects)
Projects <- Projects[names(Projects) == "Project"]
Projects_Info <- list()
for(p in seq_along(Projects)){
Project <- Projects[[p]]
Project_Name <- xmlAttrs(Project)
Project_Sample_Info <- list()
for(s in seq_along(Project)){
Sample <- Project[[s]]
Sample_Name <- xmlAttrs(Sample)
Sample_BarcodeExpected <- Sample[[1]]
Sample_BarcodeExpected_Name <- xmlAttrs(Sample[[1]])
Project_Sample_BarcodeExpected_Lane_Info <- list()
Lane_Info <- list()
for(b in seq_along(Sample_BarcodeExpected)){
Lane <- Sample_BarcodeExpected[[b]]
Lane_Name <- xmlAttrs(Lane)
Tile_Info <- list()
for(t in seq_along(Lane)){
Tile <- Lane[[t]]
Tile_Name <- xmlAttrs(Tile)
FilterState_Info <- list()
for(f in seq_along(Tile)){
FilterState <- Tile[[f]]
FilterState_Name <- xmlName(FilterState)
FilterState_ClusterCount <- as.integer(xmlValue(FilterState[["ClusterCount"]]))
ReadNumber_Info <- list()
for(r in seq_along(FilterState)[-1]){
Read <- FilterState[[r]]
ReadNumber <- xmlAttrs(Read)
ReadNumber_Yield <- as.integer(xmlValue(Read[["Yield"]]))
ReadNumber_YieldQ30 <- as.integer(xmlValue(Read[["YieldQ30"]]))
ReadNumber_QualityScoreSum <- as.numeric(xmlValue(Read[["QualityScoreSum"]]))
ReadNumber_Info[[r-1]] <- data.frame(Yield = ReadNumber_Yield,
Yield30 = ReadNumber_YieldQ30,
QualityScoreSum = ReadNumber_QualityScoreSum,
ClusterCount = FilterState_ClusterCount
)
names(ReadNumber_Info)[r-1] <- paste0("Read_",ReadNumber)
}
rniMat <- do.call(rbind,ReadNumber_Info)
rniMatDF <- data.frame(ReadNumber=rownames(rniMat),rniMat)
FilterState_Info[[f]] <- data.frame(Filter = rep(FilterState_Name,nrow(rniMatDF)),
rniMatDF)
names(FilterState_Info)[f] <- FilterState_Name
}
fsiMat <- do.call(rbind,FilterState_Info)
fsiMatDF <- data.frame(fsiMat)
Tile_Info[[t]] <- data.frame(Tile = rep(Tile_Name,nrow(fsiMatDF)),
fsiMatDF)
names(Tile_Info)[t] <- paste0("Tile_",Tile_Name)
}
tiMat <- do.call(rbind,Tile_Info)
tiMatDF <- data.frame(tiMat)
Lane_Info[[b]] <- data.frame(Lane = rep(Lane_Name,nrow(tiMatDF)),
tiMatDF)
names(Lane_Info)[b] <- paste0("Lane_",Lane_Name)
}
liMat <- do.call(rbind,Lane_Info)
liMatDF <- data.frame(liMat)
Project_Sample_Info[[s]] <- data.frame(Sample = rep(Sample_Name,nrow(liMatDF)),
liMatDF)
names(Project_Sample_Info)[s] <- paste0(Sample_Name)
}
psi2Mat <- do.call(rbind,Project_Sample_Info)
psi2MatDF <- data.frame(psi2Mat)
Projects_Info[[p]] <- data.frame(Project = rep(Project_Name,nrow(psi2MatDF)),
psi2MatDF)
names(Projects_Info)[p] <- paste0(Project_Name)
}
Projects_DF <- do.call(rbind,Projects_Info)
rownames(Projects_DF) <- NULL
return(Projects_DF)
}
return(NULL)
}
summariseDemuxStats <- function(demuxProcessed){
#Lane_Stats4 <- Test %>% filter(Sample != "all" & BarcodeStat == "BarcodeCount") %>% group_by(Project,Sample) %>% summarise(Count=sum(as.numeric(Count)))
#Lane_Stats <- Projects_DF %>% filter(Sample == "all") %>% group_by(Lane,Filter) %>% summarise(sum(Yield))
if(!is.null(demuxProcessed)){
temp <- demuxProcessed %>% tbl_df %>% mutate(Count = as.numeric(Count)) %>%
filter(Sample != "all" & BarcodeStat == "BarcodeCount") %>%
filter(Project != "default") # Computing percent label text and position for pie chart
# temp <- temp %>% group_by(Lane) %>% mutate(labelperc=round(Count/sum(Count),2)*100) %>% group_by(Lane) %>% mutate(pos = cumsum(labelperc)- labelperc/2)
# p1 <- temp %>% filter(Project != "default") %>% ggplot(aes(x=Project,y=Count,fill=Project))+geom_violin(alpha=0.3,scale="width")+geom_jitter(alpha=0.6)+theme(legend.position="bottom")
# p2 <- ggplot(temp,aes(x=Lane,y=Count,fill=Sample))+geom_bar(stat = "identity")+theme_bw()+theme(legend.position="bottom")
# p3 <- ggplot(temp,aes(x=Sample,y=Count,fill=Lane))+geom_bar(stat = "identity")+theme_bw()+coord_flip()+theme(legend.position="bottom")
# if(plot){
# print(p1)
# print(p2)
# print(p3)
# }
#return(list(Summary=temp,Boxplot=p1,StackedBar=p2,Bar=p3))
# Lane_perTileStats <- demuxProcessed %>% group_by(Lane,Tile,Filter) %>% filter(Sample != "all") %>% summarise(Yield=sum(as.numeric(Yield)))
# LaneSample_perTileStats <- demuxProcessed %>% group_by(Lane,Sample,Tile,Filter) %>% filter(Sample != "all") %>% summarise(Yield=sum(as.numeric(Yield)))
#Sample_Stats <- demuxProcessed %>% filter(Sample != "all") %>% group_by(Sample) %>% summarise(Yield=sum(as.numeric(Yield)))
#Lane_Stats <- demuxProcessed %>% filter(Sample != "all") %>% group_by(Lane) %>% summarise(Yield=sum(as.numeric(Yield)))
return(list(Summary=temp))
}
return(NULL)
}
summariseConvStats <- function(convStatsProcessed){
#Lane_Stats4 <- Test %>% filter(Sample != "all" & BarcodeStat == "BarcodeCount") %>% group_by(Project,Sample) %>% summarise(Count=sum(as.numeric(Count)))
#Lane_Stats <- Projects_DF %>% filter(Sample == "all") %>% group_by(Lane,Filter) %>% summarise(sum(Yield))
if(!is.null(convStatsProcessed)){
Lane_perTileStats <- convStatsProcessed %>% group_by(Lane,Tile,Filter) %>% filter(Sample != "all") %>% summarise(Yield=sum(as.numeric(Yield)))
LaneSample_perTileStats <- convStatsProcessed %>% group_by(Lane,Sample,Tile,Filter) %>% filter(Sample != "all") %>% summarise(Yield=sum(as.numeric(Yield)))
Sample_Stats <- convStatsProcessed %>% filter(Sample != "all") %>% group_by(Sample,Filter) %>% summarise(Yield=sum(as.numeric(Yield)))
Lane_Stats <- convStatsProcessed %>% filter(Sample != "all") %>% group_by(Lane,Filter) %>% summarise(Yield=sum(as.numeric(Yield)))
#Lane_Stats <- Projects_DF %>% filter(Sample == "all") %>% group_by(Lane,Filter) %>% summarise(sum(Yield))
#p3 <- ggplot(data=Lane_perTileStats,aes(x=Lane,y=Yield))+geom_violin()
#ggplot(data=Sample_Stats,aes(x=Sample,y=Yield,fill=Filter))+geom_boxplot()
# if(plot){
# print(p3)
# }
return(list(Lane_perTileStats=Lane_perTileStats,
LaneSample_perTileStats=LaneSample_perTileStats,
Sample_Stats=Sample_Stats,
Lane_Stats=Lane_Stats))
}
return(NULL)
}
runParameters <- function(runParameters = NULL){
xmlFromRunParameters <- xmlParse(runParameters)
currentRunParameters <- xmlToDataFrame(xmlFromRunParameters)
currentRunParameters <- currentRunParameters[!is.na(currentRunParameters$ExperimentName),,drop=FALSE]
currentRunParameters %>% tbl_df
}
