setRepositories(ind=c(1,2))
install.packages("nucim")
library(bioimagetools)
library(nucim)choose one of the files in a folder of RGB files
folder = folder.choose()scripts can use parallel computing, if available (not under Windows)
nr.cores=ifelse(.Platform$OS.type=="windows", 1, parallel::detectCores())split channels
splitchannels.folder(folder, rgb.folder="./", cores=nr.cores)masks
dapimask.folder(folder, voxelsize=c(0.0395,0.0395,0.125), cores=nr.cores)classification
classify.folder(folder, 7, cores=nr.cores)
plot_classify.folder(folder, 7, cores=nr.cores, col=heatmap7())results will be in folders “class7” and “class7-n”
class distances
nearestClassDistances.folder(folder, voxelsize=c(0.0395,0.0395,0.125), cores=nr.cores)
plot_nearestClassDistances.folder(folder, cores=nr.cores)colors in classes
colors.in.classes.folder(folder, "green", color2="red", cores=nr.cores, thresh1=0.05, thresh2=0.05, type="intensity")
plot_colors.in.classes.folder(folder,"green","red")
t_colors.in.classes.folder(folder,test="wilcox") Works also for contiguous targeted sequences
spots.combined.folder(folder, cores=nr.cores, thresh.offset=0.02, full.voxel=FALSE)
colors.in.classes.folder(folder, "markers_red", color2="markers_green", cores=nr.cores,type="i")
plot_colors.in.classes.folder(folder,"red","green")
t_colors.in.classes.folder(folder,test="wilcox")