Merge pull request #103 from ImmuneDynamics/development

Updates

workflows/Spatial - FlowJo/Spectre TIFF to FCS/TIFF to FCS.R

@@ -0,0 +1,252 @@
+###################################################################################
+### Spectre: TIFF to FCS
+###################################################################################
+
+        ### Load libraries
+
+        library('Spectre')
+
+        Spectre::package.check(type = 'spatial')
+        Spectre::package.load(type = 'spatial')
+
+        ### Set PrimaryDirectory
+
+        dirname(rstudioapi::getActiveDocumentContext()$path)            # Finds the directory where this script is located
+        setwd(dirname(rstudioapi::getActiveDocumentContext()$path))     # Sets the working directory to where the script is located
+        getwd()
+        PrimaryDirectory <- getwd()
+        PrimaryDirectory
+
+        ### Set InputDirectory (ROI TIFFs)
+
+        setwd(PrimaryDirectory)
+        setwd("../data/ROIs/")
+        InputDirectory <- getwd()
+        InputDirectory
+
+        ### Set MaskDirectory (ROI mask TIFFs)
+
+        setwd(PrimaryDirectory)
+        setwd("../data/masks")
+        MaskDirectory <- getwd()
+        MaskDirectory
+
+        ### Create output directory
+
+        setwd(PrimaryDirectory)
+        dir.create("Output - TIFF to FCS")
+        setwd("Output - TIFF to FCS")
+        OutputDirectory <- getwd()
+        OutputDirectory
+
+###################################################################################
+### Check ROIs and TIFFs
+###################################################################################
+
+        ### Initialise the spatial data object with channel TIFF files
+
+        setwd(InputDirectory)
+
+        rois <- list.dirs(full.names = FALSE, recursive = FALSE)
+        as.matrix(rois)
+
+        ### Check channel names
+
+        tiff.list <- list()
+
+        for(i in rois){
+            setwd(InputDirectory)
+            setwd(i)
+            tiff.list[[i]] <- list.files(getwd())
+        }
+
+        t(as.data.frame(tiff.list))
+
+###################################################################################
+### Read in TIFF files and create spatial objects
+###################################################################################        
+
+        ### Read in ROI channel TIFFs
+
+        setwd(InputDirectory)
+        spatial.dat <- read.spatial.files(dir = InputDirectory)
+
+        ### Check results
+
+        str(spatial.dat, 3)
+        spatial.dat[[1]]@RASTERS
+
+###################################################################################
+### Read in masks files
+###################################################################################
+
+        ### Define cell mask extension for different mask types
+
+        setwd(MaskDirectory)
+
+        all.masks <- list.files(pattern = '.tif')
+        as.matrix(all.masks)
+
+        mask.types <- list('cell.mask' = '_ilastik_s2_Object Identities.tif',
+                           'cell.type' = '_ilastik_s2_Object Predictions.tif',
+                           'region' = '_ilastik_s2_Simple Segmentation.tif')
+        mask.types
+
+        ### Read in masks
+
+        for(i in names(mask.types)){
+            spatial.dat <- do.add.masks(dat = spatial.dat, 
+                                        mask.dir = MaskDirectory, 
+                                        mask.pattern = mask.types[[i]], 
+                                        mask.label = i)
+        }
+
+        str(spatial.dat, 3)
+        str(spatial.dat[[1]]@MASKS, 3)
+
+###################################################################################
+### Rename rasters (if required)
+###################################################################################
+
+        ### Check channel names
+
+        channel.names <- list()
+
+        for(i in names(spatial.dat)){
+            channel.names[[i]] <- names(spatial.dat[[i]]@RASTERS)
+        }
+
+        t(as.data.frame(channel.names))
+
+        ### List of corrections (first entry is the 'correct' one)
+
+        # corrections <- list(c('CD4','Cd4'),
+        #                     c('CD8','CD8a')
+        #                     )
+
+        ### Replace the 'incorrect' names
+
+        # for(i in names(spatial.dat)){
+        #   # i <- names(spatial.dat)[[1]]
+        #   
+        #   for(a in c(1:length(corrections))){
+        #     # a <- 1
+        #     
+        #     trg <- which(names(spatial.dat[[i]]@RASTERS) == corrections[[a]][2])
+        #     if(length(trg) != 0){
+        #       names(spatial.dat[[i]]@RASTERS)[trg] <- corrections[[a]][1]
+        #     }
+        #   }
+        # }
+
+        ### Check channel names
+
+        # channel.names <- list()
+        # 
+        # for(i in names(spatial.dat)){
+        #   channel.names[[i]] <- names(spatial.dat[[i]]@RASTERS)
+        # }
+        # 
+        # t(as.data.frame(channel.names))      
+
+###################################################################################
+### Generate polygons and outlines
+###################################################################################
+
+        ### Generate polygons and outlines
+
+        for(i in names(spatial.dat[[1]]@MASKS)){
+            spatial.dat <- do.create.outlines(dat = spatial.dat, mask.name = i)
+        }
+
+
+        ### Checks
+
+        str(spatial.dat, 3)
+        str(spatial.dat[[1]]@MASKS, 2)
+
+###################################################################################
+### Mask QC plots
+###################################################################################       
+
+        ### Mask plot setup
+
+        setwd(OutputDirectory)
+        dir.create('Plots - cell masks')
+        setwd('Plots - cell masks')
+
+        as.matrix(names(spatial.dat[[1]]@RASTERS))
+        base <- 'DNA1_Ir191'
+        base
+
+        as.matrix(names(spatial.dat[[1]]@MASKS))
+        mask <- 'cell.mask'
+        mask    
+
+        ### Create plots
+
+        for(i in names(spatial.dat)){
+            make.spatial.plot(dat = spatial.dat, 
+                              image.roi = i, 
+                              image.channel = base, 
+                              mask.outlines = mask)
+        }
+
+###################################################################################
+### Calculate cellular data and plot
+###################################################################################       
+
+        ### Calculate cellular data for each cell mask (this step may take some time)
+
+        spatial.dat <- do.extract(spatial.dat, 'cell.mask')
+        str(spatial.dat, 3)
+
+        spatial.dat[[1]]@DATA
+
+        all.dat <- do.pull.data(spatial.dat, 'CellData')
+        all.dat
+
+###################################################################################
+### Save data
+###################################################################################       
+
+        ### Output QS and CSV file
+
+        setwd(OutputDirectory)
+        dir.create('Data')
+        setwd('Data')
+
+        qsave(spatial.dat, "spatial.dat.qs")
+        fwrite(all.dat, 'all.dat.csv')
+
+        ### Pull cellular data and write FCS file from each ROI independently
+
+        setwd(OutputDirectory)
+        dir.create('FCS files')
+        setwd('FCS files')
+
+        for(i in names(spatial.dat)){
+
+            ## Extract data and setup cols
+
+            tmp <- list()
+            tmp[[i]] <- spatial.dat[[i]]
+
+            cell.dat <- do.pull.data(tmp, 'CellData')
+            cell.dat <- do.asinh(cell.dat, names(spatial.dat[[i]]@RASTERS), cofactor = 1)
+
+            ### Invert y axis
+
+            all.neg <- function(test) -1*abs(test)
+
+            y_invert <- cell.dat[['y']]
+            y_invert <- all.neg(y_invert)
+            cell.dat[['y_invert']] <- y_invert
+
+            ### Write FCS files  
+
+            write.files(cell.dat, i, write.csv = FALSE, write.fcs = TRUE)
+            rm(cell.dat)
+            rm(i)
+        }
+

workflows/Spatial - FlowJo/metadata/sample.metadata.csv

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+ROI,Sample,Group,Batch
+ROI002,r2,Control,A
+ROI004,r4,Control,B
+ROI006,r7,Control,B
+ROI008,r8,Test,A
+ROI010,r10,Test,A
+ROI012,r12,Test,B