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plots.R
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plots.R
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#
# Small functions
#
scaleForDisplay <- function(values,lut_min,lut_max){
v = 255 * (values-as.numeric(lut_min) )/(as.numeric(lut_max)-as.numeric(lut_min) ) + 1
toosmall = which(v<1)
toolarge = which(v>255)
v[toosmall]=1
v[toolarge]=256
return(v)
}
colorbar <- function(lut, min, max, nticks=11, ticks=seq(min, max, len=nticks), newdevice = T) {
min = as.numeric(min)
max = as.numeric(max)
print ("updating color bar")
print (min)
print (max)
scale = (length(lut)-1)/(max-min)
#if(devColorBar == -1) {
# dev.new(width=1.75, height=5)
#} else {
# dev.set(devColorBar)
#}
#devColorBar <<- dev.cur()
#op <- par(mar = c(5,6,1,1) + 0.1)
if(newdevice) {
currentdev = dev.cur() # should be the plateview
dev.new(width=1.75, height=5)
}
# todo: name of measurement
plot(c(0,10), c(min,max), type='n', bty='n', xaxt='n', ylab='', yaxt='n', xlab='', main='')
axis(2, round(ticks,2), las=1) # rounding of the labels
stepsize = 10
for (i in seq(1,(length(lut)-1), by=stepsize) ) {
y = (i-1)/scale + min
rect(0, y - 0.5*(stepsize/scale), 10, y + 0.5*(stepsize/scale), col=lut[i], border=NA)
}
#par(op)
if(newdevice) {
dev.set(currentdev)
}
}
#
# Image Viewing
#
htmShowDataFromRow <- function(htm,data,irs,appendCommand=""){
if(htmGetListSetting(htm,"visualisation","viewImages") == "None selected") {
print("")
print("No image selected for viewing; see [Configure > Configure visualisation settings]")
return(0)
}
filenamePrefix = htm@settings@visualisation$image_filename_prefix
foldernamePrefix = htm@settings@visualisation$image_foldername_prefix
# convert to forward slashes immediately, otherwise gsub has problems later
rootFolderTable = gsub("\\\\" ,"/",htmGetListSetting(htm,"visualisation","image_root_foldername_in_table"))
rootFolderReal = gsub("\\\\" ,"/",htmGetListSetting(htm,"visualisation","image_root_foldername_on_this_computer"))
if( .Platform$OS.type == "unix" ) {
#imageViewerCMD = "/Applications/Fiji.app/Contents/MacOS/fiji-macosx --no-splash"
imageViewerCMD = '/Applications/Fiji.app/Contents/MacOS/ImageJ-macosx -debug '
} else if( .Platform$OS.type == "windows" ) {
imageViewerCMD = paste("\"",htm@settings@visualisation$windows_path_to_fiji,"\""," -debug ",sep="")
#imageViewerCMD = "\"c:\\Program Files\\FIJI\\fiji-win64.exe\" --no-splash -macro"
} else {
imageViewerCMD = "unkown"
}
cmd = ""
# check that the columns exist in general
filename_found = F
foldername_found = F
for ( colname in colnames(data) ) {
if( grepl(filenamePrefix,colname) ) {
filename_found = T
}
if( grepl(foldernamePrefix,colname) ) {
foldername_found = T
}
}
if ( (filename_found != T) || (foldername_found != T) ) {
gmessage("File- or Foldername columns not found. Please re-configure: [Configure > Configure Visualisation Settings]")
return(NULL)
}
for ( ir in irs) {
for ( colname in colnames(data) ) {
if( foldernamePrefix != "" ) {
# construct pathname from file- and folder-name
if( grepl(filenamePrefix, colname) ) {
imagename = strsplit(colname,filenamePrefix)[[1]][2]
filename = data[[colname]][ir]
cFolder = paste(foldernamePrefix,imagename,sep="")
#print(cFolder)
foldername = gsub("\\\\" ,"/",data[[cFolder]][ir])
foldername = gsub(rootFolderTable, rootFolderReal, foldername)
pathname = paste(foldername,"/",filename,sep="")
if(!grepl("^/", pathname)) {
pathname = paste0("/",pathname)
}
if(imagename %in% htmGetListSetting(htm,"visualisation","viewImages"))
{
#cmd = paste(cmd, paste0(' -eval \"open(\'',pathname,'\')\"') )
cmd = paste(cmd, paste0('open(\'',pathname,'\');\n') )
}
} # from file- and folder-name
} else {
# directly get the pathname=filename
if( grepl(filenamePrefix, colname) ) {
imagename = strsplit(colname,filenamePrefix)[[1]][2]
if(imagename %in% htmGetListSetting(htm,"visualisation","viewImages")) {
print(colname)
pathname = gsub("\\\\" ,"/",data[[colname]][ir])
#print(pathname)
#print(rootFolderReal)
#print(rootFolderTable)
pathname = gsub(rootFolderTable, rootFolderReal, pathname)
#print(pathname)
if ( .Platform$OS.type == "unix" ) {
pathname = gsub("\\\\" ,"/", pathname)
} else if ( .Platform$OS.type == "windows" ) {
pathname = gsub("/", "\\\\", pathname)
}
images = c(images, pathname)
if(("Location_Center_X" %in% names(data)) && ("Location_Center_Y" %in% names(data))) {
locX = c(locX, round(data$Location_Center_X[ir]))
locY = c(locY, round(data$Location_Center_Y[ir]))
} else {
locX = c(locX, 0)
locY = c(locY, 0)
}
#print(pathname)
}
}
} # from pathname
} # colname loop (within one row)
# make stack
#cmd = paste(cmd, paste0(' -eval \"run(\'Images to Stack\');\"'))
# make composite
#cmd = paste(cmd, paste0(' -eval \"run(\'Make Composite\', \'display=Composite\');\"'));
# autoscale display
#cmd = paste(cmd, paste0(' -eval \"run(\'Enhance Contrast\', \'saturated=0.01\')\"'))
if(("Location_Center_X" %in% names(data)) && ("Location_Center_Y" %in% names(data))) {
#cmd = paste(cmd,' -eval \"makePoint(',round(data$Location_Center_X[ir]),',',round(data$Location_Center_Y[ir]),');\"')
x <- round(data$Location_Center_X[ir])
y <- round(data$Location_Center_Y[ir])
#cmd = paste(cmd, paste0(' -eval \"makeRectangle(',x-50,',',y-50,',',100,',',100,');\"'))
#cmd = paste(cmd, paste0(' -eval \"run(\'Draw\', \'slice\');\"'))
cmd = paste(cmd, paste0('makeRectangle(',x-50,',',y-50,',',100,',',100,');\n'))
cmd = paste(cmd, paste0('run(\'Draw\', \'slice\');\n'))
}
} # row loop
if(length(irs)>1) {
# make stack
#cmd = paste(cmd, paste0(' -eval \"run(\'Images to Stack\');\"'))
cmd = paste(cmd, paste0('run(\'Images to Stack\');\n'))
}
tmp_path = paste0(htmPath,"/tmp")
dir.create(tmp_path, showWarnings = FALSE)
tmp_file = paste0(tmp_path,"/open.ijm");
write(cmd, file = tmp_file);
if ( .Platform$OS.type == "unix" ) {
tmp_file = gsub("\\\\" ,"/", tmp_file)
} else if ( .Platform$OS.type == "windows" ) {
tmp_file = gsub("/", "\\\\", tmp_file)
}
full_cmd = paste(imageViewerCMD,'-macro',paste0('\"',tmp_file,'\"'));
print(full_cmd)
system(full_cmd,wait=F)
}
htmShowWellsFromRow <- function(htm,data,ir){
print("Click and View:")
for(colname in colnames(data)) {
print(paste(" ",colname,"=",data[[colname]][ir]))
}
}
#
# Heatmap
#
htmShowHeatmapData <- function(htm, selectedExp="", selectedMeasurement, markQC = T, width = htm@settings@visualisation$heatmap_width,
colorLUT.autoscale = F, colorLUT.min = 0, colorLUT.max = 100, newdevice = T,
show_gradient_correction = F, action="plot") {
#
# CHECK
#
if( is.null(htm@settings@columns$wellnum) || !(htm@settings@columns$wellnum %in% colnames(htm@data)) ) {
gmessage("Error: Position/Well column not found.")
return(NULL)
}
if( is.null(htm@settings@columns$posnum) || !(htm@settings@columns$posnum %in% colnames(htm@data)) ) {
gmessage("Error: Sub-position column not found.")
return(NULL)
}
if( is.null(htm@settings@columns$experiment) ||!(htm@settings@columns$experiment %in% colnames(htm@data)) ) {
gmessage("Error: Experimental batch column not found.")
return(NULL)
}
if( is.null(htm@settings@columns$treatment) ||!(htm@settings@columns$treatment %in% colnames(htm@data)) ) {
gmessage("Error: Treatment column not found.")
return(NULL)
}
#
# Get data
#
dat <- subset(htm@data,(htm@data[[htm@settings@columns$experiment]]==selectedExp))
dat[[selectedMeasurement]] = as.numeric( dat[[selectedMeasurement]] )
dat[[htm@settings@columns$posnum]] = as.numeric( dat[[htm@settings@columns$posnum]] )
if(!any(grepl("(?i)[A-Z]", dat[[htm@settings@columns$wellnum]]))) {
dat[[htm@settings@columns$wellnum]] = as.numeric( dat[[htm@settings@columns$wellnum]] )
}
if(colorLUT.autoscale == T) {
colorLUT.min <- quantile(dat[[selectedMeasurement]], 0.03, na.rm=T) #min(dat, na.rm=T)
colorLUT.max <- quantile(dat[[selectedMeasurement]], 0.97, na.rm=T) #max(dat, na.rm=T)
}
print("")
print("Show heatmap:")
print("*************")
print(paste("selected Experiment =",selectedExp))
print(paste("selected Measurement =",selectedMeasurement))
print(paste("colorLUT.min =",colorLUT.min))
print(paste("colorLUT.max =",colorLUT.max))
dat$val = 255*(dat[[selectedMeasurement]]-as.numeric(colorLUT.min) )/(as.numeric(colorLUT.max)-as.numeric(colorLUT.min) )
toosmall = which(dat$val<1)
toolarge = which(dat$val>255)
dat$val[toosmall]=1
dat$val[toolarge]=255
colpal <- colorRampPalette(c("blue","white","red"))(255)
plate.nrow = htm@settings@visualisation$number_positions_y
plate.ncol = htm@settings@visualisation$number_positions_x
#par(mar=c(5.1,6.1,6.1,2.1))
xy = htm_convert_wellNum_posNum_to_xy(dat[[htm@settings@columns$wellnum]],dat[[htm@settings@columns$posnum]])
if(action=="plot") {
if(newdevice) {
dev.new(width = 1.5 * width, height = plate.nrow / plate.ncol * width)
}
op <- par(bg = "grey")
plot(x = xy$x, y = xy$y, col=colpal[dat$val],
ylim = rev(range(xy$y)),
xlim = round(range(xy$x)),
xaxt = "n", yaxt = "n", xaxs = "i",
pch = 15, cex= htm@settings@visualisation$heatmap_image_size_cex, xlab="", ylab="",
asp = 1
)
title(paste(selectedExp,selectedMeasurement,sep="\n"),cex.main=1)
axis(1, at=1:plate.ncol, labels=1:plate.ncol, las=1, cex.axis = 1)
axis(2, at=1:plate.nrow, labels=LETTERS[1:plate.nrow], las=2, cex.axis = 1)
par(op)
#todo: change qcImages to ImageQC
if(markQC) {
if(!is.null(dat$HTM_qc)) {
print(" adding image QC.")
ids <- which(dat$HTM_qc==0)
x <- vector(length=length(ids))
y <- vector(length=length(ids))
for (i in seq(1,length(ids))) {
x[i] <- xy$x[ids[i]]
y[i] <- xy$y[ids[i]]
}
points(x, y, pch=4, cex=1*htm@settings@visualisation$heatmap_image_size_cex)
} else {
print(" no image QC available.")
}
# well QC
if(!is.null(dat$HTM_qcWells)) {
print(" adding well QC.")
for (i in which(dat$HTM_qcWells==0)) {
points(xy$x[i], xy$y[i], pch=4, cex=htm@settings@visualisation$heatmap_image_size_cex * htm@settings@visualisation$number_subpositions_x)
}
} else {
print(" no well QC available.")
}
# plate QC
if(!is.null(dat$HTM_qcPlates)) {
print(" adding plate QC.")
if(dat$HTM_qcPlates[1]==0) {
points(x=mean(xy$x),y=mean(xy$y), pch=4, cex=100)
}
} else {
print(" no plate QC available.")
}
} # if markQC
} # if action=="plot"
if (action=="click") {
print("please select an image for viewing!")
i <- identify(xy$x, xy$y, n = 1, plot = FALSE)
print(" ")
print(paste("experiment =", dat[[htm@settings@columns$experiment]][i]))
print(paste("treatment =", dat[[htm@settings@columns$treatment]][i]))
print(paste(selectedMeasurement,"=", dat[[selectedMeasurement]][i]))
print(" ")
htmShowDataFromRow(htm,dat,i)
}
} #htmShowHeatmapData
htmMakeAllHeatmaps <- function(htm, datatype = "images", measurement, path, markQC = T, colorLUT.min=0, colorLUT.max=1, colorLUT.autoscale=F, selectTreat1, selectTreat2, selectTreat3) {
experiments <- sort(unique(htm@data[[htm@settings@columns$experiment]]))
print("");print("Experiments:")
print(experiments)
print(paste("Plot width:",htm@settings@visualisation$heatmap_width))
#print(paste("Plot height:",htm@settings@visualisation$heatmap_height))
# check experiments we know everything
if( is.null(experiments) |
is.na(htm@settings@visualisation$heatmap_width)
#is.na(htm@settings@visualisation$heatmap_height)
) {
print("")
print(" ERROR: cannot perform job due to lacking information (see above).")
return(NULL)
}
pdf(file = path,
width = htm@settings@visualisation$heatmap_width,
height = htm@settings@visualisation$number_positions_y / htm@settings@visualisation$number_positions_x * htm@settings@visualisation$heatmap_width
)
# plot color bar in front
if(!(colorLUT.autoscale==T)) {
colorbar(colorRampPalette(c("blue","white","red"))(255), min=colorLUT.min, max=colorLUT.max, newdevice=F)
}
for(experiment in experiments) {
print("")
print(paste("Experiment :",experiment))
htmShowHeatmap(htm=htm,
datatype = datatype,
selectedExp = experiment,
selectedMeasurement = measurement,
markQC = markQC,
colorLUT.autoscale = colorLUT.autoscale,
colorLUT.min = colorLUT.min,
colorLUT.max = colorLUT.max,
newdevice = F)
htmHeatmap_MarkSelectedTreatment(htm=htm,
selectedExp=experiment,
selectedTreatment=selectTreat1,
color = "black")
htmHeatmap_MarkSelectedTreatment(htm=htm,
selectedExp=experiment,
selectedTreatment=selectTreat2,
color = "white")
htmHeatmap_MarkSelectedTreatment(htm=htm,
selectedExp=experiment,
selectedTreatment=selectTreat3,
color = "green")
} # exp
dev.off()
}
htmHeatmap_MarkSelectedTreatment <- function(htm, selectedExp, selectedTreatment, color="black") {
print(paste("selected treatment = ",selectedTreatment))
if(!selectedTreatment=="None selected") {
dat <- subset(htm@data,htm@data[[htm@settings@columns$experiment]]==selectedExp);
ids = which(dat[[htm@settings@columns$treatment]]==selectedTreatment)
n = length(ids)
if(n>0) {
x <- vector(length=n)
y <- vector(length=n)
xy = htm_convert_wellNum_to_xy(dat[[htm@settings@columns$wellnum]])
for (i in seq(n)) {
x[i] <- xy$x[ids[i]]
y[i] <- xy$y[ids[i]]
}
print("mark")
points(x, y,
pch = 22,
lwd = 2.25,
cex = 1.1 * htm@settings@visualisation$heatmap_image_size_cex * max(c(htm@settings@visualisation$number_subpositions_x,htm@settings@visualisation$number_subpositions_y)),
col = color) #22 = empty rectangle
}
}
}
#
# Jitter-plot
#
htmJitterplot_Data <- function(htm=htm, cx, cy, .xlab="", .ylab="", treatmentSubset = "None selected",
.xlim=NA, .ylim=NA, colorizeTreatments=F,
sorting="None selected", experimentSubset="None selected", newdev = T,
action="plot", printMeanSD = T, showMean = T, showMedian = T, save2file = F,
scaleFromZero = F, reference="None selected") {
print("")
print("")
print("")
print("")
print("Jitter Plot:")
print(paste(" x =",cx))
print(paste(" y =",cy))
if("All treatments" %in% treatmentSubset) {
treatmentSubset = "None selected"
}
# subsample
if(is.numeric(htmGetListSetting(htm,"visualisation","jitterPlot_subsample",gui=T))) {
every_nth = htmGetListSetting(htm,"visualisation","jitterPlot_subsample",gui=T)
data <- htm@data[seq(1,nrow(htm@data),every_nth), ]
} else {
data <- htm@data
}
if(experimentSubset[1] != "None selected") {
print(paste(" selecting experiments:",experimentSubset))
data <- subset(data, data[[htm@settings@columns$experiment]] %in% experimentSubset)
}
if(treatmentSubset[1] != "None selected") {
print(paste(" selecting treatments:",treatmentSubset))
data <- subset(data, data[[htm@settings@columns$treatment]] %in% treatmentSubset)
}
if(!is.null(htm@settings@columns$treatment)) treatments <- data[[htm@settings@columns$treatment]]
qc <- data$HTM_qc
if(!is.null(qc)) {
print(" qc column exists")
} else {
print(" no qc column => evaluate all data")
qc = rep(1, nrow(data))
}
print(paste(" sorting:",sorting))
if(sorting=="None selected") {
ids = 1:nrow(data)
}
if(sorting=="alphabetic") {
print(" applying alphabetic sorting")
#print(factor(data[[cx]]))
ids <- order(data[[cx]],na.last=NA)
}
if(sorting=="median value") {
print(" applying median sorting")
#print(unique(factor(data[[cx]])))
ids_cx = split(1:nrow(data),data[[cx]])
data$medians = rep(NA,nrow(data))
for(ids in ids_cx) {
#values = subset(data[ids,],qc[ids]==1,select=cy)[[1]]
#print(values)
if(!is.null(qc)) {
values = data[ids,cy][which(qc[ids]==1)]
} else {
values = data[ids,cy]
}
data$medians[ids] = rep(median(values, na.rm = T),length(ids))
}
ids <- order(data$medians,na.last=NA)
}
if(sorting=="mean value") {
print(" applying mean sorting")
#print(unique(factor(data[[cx]])))
ids_cx = split(1:nrow(data),data[[cx]])
data$means = rep(NA,nrow(data))
for(ids in ids_cx) {
#values = subset(data[ids,],qc[ids]==1,select=cy)[[1]]
#print(values)
if(!is.null(qc)) {
values = data[ids,cy][which(qc[ids]==1)]
} else {
values = data[ids,cy]
}
data$means[ids] = rep(mean(values, na.rm = T),length(ids))
}
ids <- order(data$means,na.last=NA)
}
# add jitter to sorted data
print(" prepare plotting..")
factors <- factor(data[ids,cx], levels=unique(data[ids,cx])); #print(factors)
if(action=="plot") {
print(" adding jitter")
jp.x <- jitter(as.numeric(factors),htm@settings@visualisation$jitter)
htm <- get("htm", envir = globalenv()) # remember for click&view
htm@settings@visualisation$jp.x <- jp.x
assign("htm", htm, envir = globalenv())
}
if(action=="click") {
print(" taking stored jitter")
htm <- get("htm", envir = globalenv())
jp.x <- htm@settings@visualisation$jp.x
}
lx = levels(factors);
jp.y <- data[ids,cy]
qc <- qc[ids]
# log2 transform if wished
if(htmGetListSetting(htm,"visualisation","jitterPlot_log2_TF")==T) {
jp.y <- log2(jp.y)
.ylab <- paste(.ylab,"[log2]")
}
print(paste(" colorizeTreatments:",colorizeTreatments==T))
if(colorizeTreatments == T) {
treatments <- treatments[ids]
print(" colorizing by treatment")
.colors = factor(treatments, levels=unique(treatments))
n = length(levels(.colors))
if(n<=8) {
col_pal <- brewer.pal(8,"Set2")
} else {
col_pal <- rainbow(n)
}
.colors = col_pal[factor(.colors)]
} else {
.colors = rep("grey30", nrow(data))
}
# compute some statistics for printing and plotting
jp.y.qc <- ifelse(qc==1, jp.y, NA)
jp.x.qc <- ifelse(qc==1, jp.x, NA)
# compute stats for plotting
jp.xMean = tapply(jp.x.qc, factors, function(z) {mean(z,na.rm=T)})
jp.yMean = tapply(jp.y.qc, factors, function(z) {mean(z,na.rm=T)})
jp.ySD = tapply(jp.y.qc, factors, function(z) {sd(z,na.rm=T)})
jp.yMedian = tapply(jp.y.qc, factors, function(z) {median(z,na.rm=T)})
jp.yMAD = tapply(jp.y.qc, factors, function(z) {mad(z,na.rm=T)})
jp.ySEM = tapply(jp.y.qc, factors, function(z) {sem(z)})
jp.ySEMabove = tapply(jp.y.qc, factors, function(z) {sem_above(z)})
jp.ySEMbelow = tapply(jp.y.qc, factors, function(z) {sem_below(z)})
jp.nOK = tapply(jp.y.qc, factors, function(z) {sum(z/z, na.rm=T)})
jp.nAll = tapply(jp.y, factors, function(z) {length(z)})
# compute t-tests
if(reference != "None selected") {
print("")
print("### T-Test:")
factors <- factor(data[ids,cx], levels=unique(data[ids,cx])); #print(factors)
idsRef = which(factors==reference)
if(sum(idsRef)>0) {
# print(paste("Reference:",reference))
print("")
m.ctrl = mean(jp.y.qc[idsRef],na.rm=T)
sd.ctrl = sd(jp.y.qc[idsRef],na.rm=T)
median.ctrl = median(jp.y.qc[idsRef],na.rm=T)
mad.ctrl = mad(jp.y.qc[idsRef],na.rm=T)
#print(jp.y.qc[idsRef])
print(paste(reference," mean =",m.ctrl," sd =",sd.ctrl))
print("")
for(factor in levels(factors)) {
#if(!factor==reference) {
idsTest = which(factors==factor)
tt <- t.test(x=jp.y.qc[idsRef],y=jp.y.qc[idsTest])
m.test = mean(jp.y.qc[idsTest],na.rm=T)
sd.test = sd(jp.y.qc[idsTest],na.rm=T)
#median.test = median(jp.y.qc[idsTest],na.rm=T)
#mad.test = mad(jp.y.qc[idsTest],na.rm=T)
#zFactor = round(1 - 3*(sd.ctrl+sd.test)/abs(m.ctrl-m.test),2)
#zScore = round(abs(m.test-m.ctrl)/sd.ctrl,2)
#robust_zScore = round(abs(median.test-median.ctrl)/mad.ctrl,2)
significance = ""
if(tt$p.value < 0.05) significance = "(*)"
if(tt$p.value < 0.01) significance = "(**)"
#print(paste(factor,"; Z-score = ",zScore,"; Robust Z-score = ",robust_zScore,"; Z-factor = ",zFactor,"; T-test = ",round(tt$p.value,4),significance))
#print(paste(factor,"; T-test = ",round(tt$p.value,10),significance))
#print(paste(factor," mean =",m.ctrl," sd =",sd.ctrl))
print(paste(factor," mean =",m.test," t-test vs.",reference,"=",tt$p.value,significance))
#print(jp.y.qc[idsTest])
#}
}
} else {
print(paste("no reference treatments found for:",reference))
}
} else {
#print("no valid Reference selected.")
}
#
# QC
#
if(htmGetListSetting(htm,"visualisation","plotting_showQCfailData_TF")==T) { # label data points that did not pass QC
pchQC = ifelse(qc==1, 16, 4)
} else { # remove data points that did not pass QC
vxTmp = jp.x[which(qc==1)]
vyTmp = jp.y[which(qc==1)]
colorsTmp = .colors[which(qc==1)]
print(length(ids))
idsTmp = ids[which(qc==1)]
ids = idsTmp
print(length(ids))
.colors = colorsTmp
jp.x = vxTmp
jp.y = vyTmp
pchQC = rep(16, length(jp.x))
print(paste("removed data points due to QC",sum(qc==0)))
}
if(action=="plot") {
if(save2file) {
path = gfile("Save as...", type="save", initialfilename = paste0("Controls_per_experiment--",htmGetListSetting(htm,"statistics","transformation"),"--",htmGetListSetting(htm,"statistics","measurement"),".pdf"))
pdf(file=path)
print(path)
} else if(newdev){
dev.new()
}
#cat(paste("\n\njitter-plotting",cy,"vs.",cx,"\n"))
op <- par(mar=c(12.1, 4.1, 4.1, 2.1), xpd=TRUE) #par(mar = c(8,5,4,2) + 0.1)
dotsize = 0.5
#pchQC = '.'
if( is.na(.xlim) || is.na(.ylim) ) {
if(htmGetListSetting(htm,"visualisation","jitterPlot_scaleFromZero_TF")==T) {
print(paste(" scaling y-axis from 0 to",max(jp.y,na.rm=T)))
plot(jp.x, jp.y, type = "p", xaxt = "n", xlab=.xlab, ylab=.ylab, ylim = c(0, max(jp.y,na.rm=T)), pch=pchQC, cex=dotsize, col = .colors, cex.lab = 1)
} else {
print(unique(pchQC))
plot(jp.x, jp.y, type = "p", xaxt = "n", xlab=.xlab, ylab=.ylab, pch = pchQC, cex=dotsize, col = .colors, cex.lab = 1)
}
} else { # zooming
plot(jp.x, jp.y, type = "p", xaxt = "n", xlab=.xlab, ylab=.ylab, xlim=.xlim, ylim=.ylim, pch=pchQC, cex=dotsize, col=.colors, cex.lab =1)
}
axis(1, at=1:length(lx), labels=lx, las=2, cex.axis = 1)
plotTitle = ""
if(experimentSubset[1] != "None selected") {
plotTitle = experimentSubset[1]
} else {
plotTitle = "All experiments"
}
if(treatmentSubset[1] != "None selected") {
plotTitle = paste(plotTitle,paste(treatmentSubset,collapse=" "),sep="\n")
} else {
plotTitle = paste(plotTitle,"All treatments",sep="\n")
}
if(is.numeric(htmGetListSetting(htm,"visualisation","jitterPlot_subsample",gui=T))) {
plotTitle = paste(plotTitle,paste("subsampling by",htmGetListSetting(htm,"visualisation","jitterPlot_subsample",gui=T)),sep="\n")
}
title(plotTitle, cex.main = 0.8)
if(colorizeTreatments == T) {
print(" putting legend")
treatments <- treatments[ids]
legend("topleft", inset=c(0,0), legend = levels(factor(treatments)), bg="white", col=col_pal, pch=16, bty="n")
}
d = 0.2
if(showMedian==T) {
#print(" median=blue")
print(" plotting Median and MAD in blue")
segments(jp.xMean-d,jp.yMedian,jp.xMean+d,jp.yMedian,col="blue",lwd=4)
segments(jp.xMean-d,jp.yMedian+jp.yMAD,jp.xMean+d,jp.yMedian+jp.yMAD,col="blue",lwd=2)
segments(jp.xMean-d,jp.yMedian-jp.yMAD,jp.xMean+d,jp.yMedian-jp.yMAD,col="blue",lwd=2)
}
if(showMean==T) {
print(" ploting Mean and SD in green")
segments(jp.xMean-d,jp.yMean,jp.xMean+d,jp.yMean,col="darkgreen",lwd=4)
segments(jp.xMean-d,jp.yMean+jp.ySD,jp.xMean+d,jp.yMean+jp.ySD,col="green",lwd=2)
segments(jp.xMean-d,jp.yMean-jp.ySD,jp.xMean+d,jp.yMean-jp.ySD,col="green",lwd=2)
}
par(op)
} # plot
if(action=="click") {
i <- identify(jp.x, jp.y, n = 1, plot = FALSE)
print("")
print(paste(cx,"=",data[ids[i],cx]))
print(paste(cy,"=",data[ids[i],cy]))
print(paste("treatment =",treatments[ids[i]]))
htmShowDataFromRow(htm,data[ids,],i)
}
if(save2file) {
dev.off()
}
}
#
# Scatter-plot
#
htmScatterPlot_Data <- function(htm, cx, cy, .xlim=NA, .ylim=NA, colorize="None selected", aggregate = "None selected", experimentSubset="None selected", treatmentSubset="None selected", newdev=T, action="plot") {
print("")
print("")
print("Scatter Plot")
data <- htm@data
if(experimentSubset[1] != "None selected") data <- subset(data, data[[htm@settings@columns$experiment]] %in% experimentSubset)
if(treatmentSubset[1] != "None selected") data <- subset(data, data[[htm@settings@columns$treatment]] %in% treatmentSubset)
qc <- data$HTM_qc
treatments <- data[[htm@settings@columns$treatment]]
experiments <- data[[htm@settings@columns$experiment]]
if(aggregate != "None selected") {
vx <- tapply(htm@data[[cx]], htm@data[[aggregate]], mean, na.rm=TRUE)
vy <- tapply(htm@data[[cy]], htm@data[[aggregate]], mean, na.rm=TRUE)
} else {
vx <- data[[cx]]
vy <- data[[cy]]
}
if( colorize != "None selected") {
if(aggregate != "None selected") {
.colors <- tapply(htm@data[[colorize]], htm@data[[aggregate]], function(z) {z[1]})
} else {
.colors = data[[colorize]]
}
n = length(unique(data[[colorize]]))
if(n<=8) {
col_pal <- brewer.pal(8,"Set2")
} else {
col_pal <- rainbow(n)
}
.colors = col_pal[factor(.colors)]
} else {
.colors = rep(1, length(vx))
}
if(!is.null(qc)) {
print(" ..qc column exists!")
if(htmGetListSetting(htm,"visualisation","plotting_showQCfailData_TF")==T) { # label data points that did not pass QC
pchQC = ifelse(qc==1, 16, 4)
} else { # remove data points that did not pass QC
print(" not showing data points that failed QC")
vx = vx[which(qc==1)]
vy = vy[which(qc==1)]
data = data[which(qc==1),]
.colors = .colors[which(qc==1)]
treatments = treatments[which(qc==1)]
qc <- rep(1,length(vx))
pchQC = rep(16, length(vx))
}
} else {
print(" ..no qc column => show all data")
pchQC = rep(16,length(vx))
}
if(action=="plot") {
#factors <- factor(treatments, levels=unique(treatments))
#palette(rainbow(length(unique(treatments))))
if(newdev){
dev.new()
}
dotsize = 0.75
op <- par(mar = c(10,10,4,2) + 0.1)
if(htmGetListSetting(htm,"visualisation","scatterPlot_scaleFromZero_TF")==T) {
.ylim = c(0, max(vy))
.xlim = c(0, max(vx))
}
type = "p"
# actual plotting
if( is.na(.xlim) || is.na(.ylim) ) {
plot(vx, vy, xlab=cx, ylab=cy, type = type, pch=pchQC, cex=dotsize, main="", col=.colors, cex.lab=1.2)
} else {
plot(vx, vy, xlab=cx, ylab=cy, xlim=.xlim, ylim=.ylim, type = type, pch=pchQC, cex=dotsize, main="", col=.colors, cex.lab=1.2)
}
if( htmGetListSetting(htm,"visualisation","scatterPlot_showTreatmentMean_TF")==T) {
factors <- factor(treatments, levels=unique(treatments))
# compute stats for plotting
vxMean = tapply(vx[which(qc==1)], factors[which(qc==1)], function(z) {mean(z,na.rm=T)})
vyMean = tapply(vy[which(qc==1)], factors[which(qc==1)], function(z) {mean(z,na.rm=T)})
colorsMean = tapply(.colors[which(qc==1)], factors[which(qc==1)], function(z) {z[1]})
points(vxMean, vyMean, pch = 16, type = type, cex = 5*dotsize, main="", col=colorsMean)
cat("\nMean values:\n")
print(vxMean)
print(vyMean)
}
plotTitle = ""
if(experimentSubset[1] != "None selected") {
plotTitle = experimentSubset[1]
} else {
plotTitle = "All experiments"
}
if(treatmentSubset[1] != "None selected") {
plotTitle = paste(plotTitle,paste(treatmentSubset,collapse=" "),sep="\n")
} else {
plotTitle = paste(plotTitle,"All treatments",sep="\n")
}
title(plotTitle, cex.main = 1.2)
linefit = TRUE
if(linefit) {
fit <- lm(vy~vx)
print(fit$coefficients)
yfit = predict(fit, list(vx=vx))
lines(vx,yfit,col="red",lwd=2)
#fit <- lm(vx~vy)
#print(fit)
#xfit = predict(fit, list(vy=vy))
#lines(xfit,vy,col="blue",lwd=2)
#pcaFit(vx,vy)
}
squarefit = TRUE
if(squarefit) {
}
#
# Print values to console
#
print(paste(as.character(vx), collapse=", "))
print(paste(as.character(vy), collapse=", "))
cat(paste(shQuote(treatments, type="cmd"), collapse=", "))
correlation = cor( vx[which(qc==1)], vy[which(qc==1)], use="complete" )
cat( paste0("\nCorrelation: ",correlation,"\n") )
if( colorize != "None selected" ) {
legend("topleft",legend = levels(factor(data[[colorize]])), bg="white", col=col_pal, pch=16)
}
par(op)
}
if(action=="click") {
print("")
i <- identify(vx, vy, n = 1, plot = FALSE)
print(paste(cx,"=",data[i,cx]))
print(paste(cy,"=",data[i,cy]))
print(paste("treatment =",treatments[i]))
htmShowDataFromRow(htm, data, i)
}
}
#
# Correlation-plot
#
htmCorrelationPlot <- function(htm, cm, corder, batchX, batchY, .xlim=NA, .ylim=NA, colorize="None selected", aggregate = "None selected", treatmentSubset="None selected", newdev=T, action="plot") {