# #——style-knitr eval = TRUE,呼应= FALSE,结果=“黑名单”- - - - - - - - - - - - - - - - - - - - - BiocStyle::乳胶()# #——loading-confess,警告= FALSE,消息= FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -库(承认)# #——readfiles - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - data_path <执行(“extdata”,包=“CONFESSdata”)文件< -readFiles (iDirectory = NULL, BFdirectory =粘贴(data_path“/男朋友”,9月= " "),CHdirectory =粘贴(data_path“/ CH”, 9月= " "),分离器=“_”形象。类型= c(“男朋友”、“绿色”、“红色”),位= 2 ^ 16)# #——spotestimator, eval = FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - #估计<——spotestimator(文件=文件、foregroundCut = seq (0.6, 0.76, 0.02), # BFarea = 7, correctionAlgorithm = FALSE, savePlot =“屏幕”)# #——dlc, eval = FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # clu <——defineLocClusters (LocData =估计,out.method =“interactive.manual”) # #”回车进入下一个图像或一个+ Enter中止:“# #——spotestimator2, eval = FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - #估计。2 < - spotEstimator(文件=文件子集= clu Outlier.indices美元,foregroundCut = seq (0.6, 0.76, 0.02), # correctionAlgorithm = TRUE, QCdata = clu, savePlot =“屏幕”)# #——locationmatrix - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - < - locationmatrix (data =估计结果。2、过滤器。=矩阵(c(“罗斯福”、“Out.Index”, 0.005,“信心”),ncol = 2))结果输出美元[1:3],# #——createfluo - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - step1 < - createfluo (from.file =系统。文件(“extdata”、“Results_of_image_analysis。txt”,包= "承认"),分离器=“_”)# #——checkbatch - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -打印(独特的(步骤1批美元))# #——fluo_adjustment, eval = FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - #步骤2 < -Fluo_adjustment (data = step1变换=“日志”,maxMix = 3, prior.pi = 0.1, # flex。代表= 50,single.batch。分析= 5 # savePlot =“屏幕”,种子= 999)# #——gf, fig.show =“隐藏”,无花果。保持= "没有" - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - step2.1 < -getFluo (data =步骤2)step3 <——Fluo_inspection (data = step2.1 altFUN =“kmeans B.kmeans = 5, savePlot =“屏幕”)# #——step345 fig.show =“隐藏”,无花果。保持= "没有" - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - step3.1 < -pathEstimator(步骤3,path.start = 3, path.type = c(“圆”,“顺时针”)第四< -Fluo_modeling (data = step3.1 init.path = step3.1路径,美元VSmethod =“DDHFmv CPmethod =“ECP”, CPgroups = 5, CPpvalue = 0.01, CPmingroup = 10)第五< -Fluo_ordering (data = step4 savePlot =“屏幕”)# #——summout - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -头(顾不上Summary_results美元,3)# #——singlebatch, eval = FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # step1.1 < -FluoSelection_byRun (data = step1、批= 1)#步骤2 < -getFluo_byRun (data = step1.1 BGmethod =“normexp savePlot =“屏幕”)# step3 < -Fluo_inspection (data =步骤2,fixClusters = 0, altFUN =“kmeans”, k。max = 15 # savePlot =“屏幕”)# step3.1 < - pathEstimator(步骤3,path.start = 2, path.type = c(“圆”,“顺时针”))#第四< - Fluo_modeling (data = step3.1 init.path = step3.1路径,美元VSmethod =“DDHFmv”, # CPmethod =“ECP”, CPpvalue = 0.01) #顾不上< -Fluo_ordering (data = step4 savePlot =“屏幕”)# #——cv1, eval = FALSE - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # step1 < - createFluo (from.file =系统。文件(“extdata”、“Results_of_image_analysis。txt”, #包= "承认"))# steps2_4 < -Fluo_CV_prep(数据= step1 init。路径=代表(“左/底”,2),# path.type = c(“圆”,“顺时针”),maxMix = 3, # single.batch。分析= 5,变换= "日志",之前。π= 0.1,# flex。代表= 5,areacut = 49岁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") ## ----cv2,fig.show="hide",message=FALSE,results="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")