## ----warning=FALSE,message=FALSE----------------------------------------- library(CONFESS) ## ----eval=FALSE---------------------------------------------------------- # library(CONFESSdata) # data_path<-system.file("extdata",package="CONFESSdata") # files<-readFiles(iDirectory=NULL, # BFdirectory=paste(data_path,"/BF",sep=""), # CHdirectory=paste(data_path,"/CH",sep=""), # separator = "_",image.type = c("BF","Green","Red"), # bits=2^16) ## ----eval=FALSE---------------------------------------------------------- # estimates <- spotEstimator(files=files,foregroundCut=seq(0.6,0.76,0.02), # BFarea=7,correctionAlgorithm=FALSE,savePlot="screen") ## ----eval=FALSE---------------------------------------------------------- # clu <- defineLocClusters(LocData=estimates,out.method="interactive.manual") # #"Hit Enter to move to the next image or A + Enter to Abort:" ## ----eval=FALSE---------------------------------------------------------- # estimates.2 <- spotEstimator(files=files,subset=clu$Outlier.indices, # foregroundCut=seq(0.6,0.76,0.02),correctionAlgorithm=TRUE, # cutoff=50,QCdata=clu,median.correction=TRUE, # savePlot="screen") ## ------------------------------------------------------------------------ Results <- LocationMatrix(data=estimates.2, filter.by = matrix(c("FDR","Out.Index",0.005,"confidence"),ncol=2)) Results$Output[1:3,] ## ------------------------------------------------------------------------ # step1 <-createFluo(Results) #from previous section's results step1 <- createFluo(from.file=system.file("extdata", "Results_of_image_analysis.txt", package = "CONFESS"),separator="_") ## ------------------------------------------------------------------------ print(unique(step1$batch)) ## ----eval=FALSE,results="hide"------------------------------------------- # step2<-Fluo_adjustment(data=step1,transformation="log",maxMix=3,prior.pi=0.1, # flex.reps = 50, single.batch.analysis=5, # savePlot="screen",seed=999) ## ----fig.show="hide"----------------------------------------------------- step2.1<-getFluo(data=step2) step3<-Fluo_inspection(data=step2.1,fixClusters=0,altFUN="kmeans", k.max=15,B.kmeans=50,savePlot="screen") ## ----fig.show="hide"----------------------------------------------------- step3.1<-pathEstimator(step3,path.start=3,path.type=c("circular","clockwise"), joinedGroups=NULL) step4<-Fluo_modeling(data=step3.1,init.path=step3.1$Path,VSmethod="DDHFmv", CPmethod="ECP",CPgroups=5,CPpvalue=0.01,CPmingroup=10) step5<-Fluo_ordering(data=step4,savePlot="screen") ## ------------------------------------------------------------------------ head(step5$Summary_results,3) ## ----eval=FALSE---------------------------------------------------------- # step1.1<-FluoSelection_byRun(data=step1,batch=1) # step2<-getFluo_byRun(data=step1.1,BGmethod="normexp",savePlot="screen") # step3<-Fluo_inspection(data=step2,fixClusters=0,altFUN="kmeans",k.max=15, # savePlot="screen") # step3.1 <- pathEstimator(step3,path.start=2,path.type=c("circular","clockwise")) # step4 <- Fluo_modeling(data=step3.1,init.path=step3.1$Path,VSmethod="DDHFmv", # CPmethod="ECP",CPpvalue=0.01) # step5<-Fluo_ordering(data=step4,savePlot="screen") ## ----eval=FALSE---------------------------------------------------------- # step1 <- createFluo(from.file=system.file("extdata", "Results_of_image_analysis.txt", # package = "CONFESS")) # steps2_4<-Fluo_CV_prep(data=step1,init.path = rep("bottom/left",2), # path.type=c("circular","clockwise"),maxMix=3, # single.batch.analysis = 5,transformation = "log",prior.pi = 0.1, # flex.reps=5,areacut=49,fixClusters=0,altFUN="kmeans", # k.max=15,VSmethod="DDHFmv",CPmethod="ECP",CPgroups=5, # B.kmeans=5,CPpvalue=0.01,CPmingroup=15,savePlot="OFF",seed=999) # steps2_4cv.1<-Fluo_CV_modeling(data=steps2_4,B=10,batch=1:4,perc.cutoff=0.6,q=0.9, # f=0.99,seed.it=TRUE,pseudotime.cutoff=20,savePlot="screen") ## ----results="hide",message=FALSE,fig.show="hide"------------------------ steps2_4cv.2<-Fluo_CV_modeling(data=steps2_4,B=1,batch=1:4,perc.cutoff=0.6,q=0.9, f=0.99,seed.it=TRUE,pseudotime.cutoff=20,savePlot="screen")