## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, fig.width = 8, fig.height = 6) ## ----stage0, results = 'hide', message = FALSE-------------------------------- library(flowClust) library(flowCore) ## ----stage1------------------------------------------------------------------- data(rituximab) summary(rituximab) res1 <- flowClust( rituximab, varNames = c("FSC.H", "SSC.H"), K = 1, B = 100 ) ## ----stage2------------------------------------------------------------------- rituximab2 <- rituximab[rituximab %in% res1, ] res2 <- flowClust( rituximab2, varNames = c("FL1.H", "FL3.H"), K = 1:6, B = 100 ) ## ----stage2Result------------------------------------------------------------- criterion(res2, "BIC") summary(res2[[3]]) ## ----stage2ChangeRule1-------------------------------------------------------- ruleOutliers(res2[[3]]) <- list(level = 0.95) summary(res2[[3]]) ## ----stage2ChangeRule2-------------------------------------------------------- ruleOutliers(res2[[3]]) <- list(z.cutoff = 0.6) summary(res2[[3]]) ## ----stage2Alternative-------------------------------------------------------- flowClust( rituximab2, varNames = c("FL1.H", "FL3.H"), K = 2, B = 100, min = c(0, 0), max = c(400, 800) ) ## ----stage2Scatter------------------------------------------------------------ plot(res2[[3]], data = rituximab2, level = 0.8, z.cutoff = 0) ## ----stage2Contour------------------------------------------------------------ res2.den <- density(res2[[3]], data = rituximab2) plot(res2.den) ## ----stage2Image-------------------------------------------------------------- plot(res2.den, type = "image") ## ----stage2Hist--------------------------------------------------------------- hist(res2[[3]], data = rituximab2, subset = "FL1.H") ## ----stage2Hist2-------------------------------------------------------------- hist(res2[[3]], data = rituximab2, subset = 1) ## ----stage2f------------------------------------------------------------------ s2filter <- tmixFilter("s2filter", c("FL1.H", "FL3.H"), K = 3, B = 100) res2f <- filter(rituximab2, s2filter) ## ----stage2fSubsetting, warning=FALSE----------------------------------------- Subset(rituximab2, res2f) split(rituximab2, res2f, population = list(sc1 = 1:2, sc2 = 3)) ## ----stage2fRectGate---------------------------------------------------------- rectGate <- rectangleGate( filterId = "rectRegion", "FL1.H" = c(0, 400), "FL3.H" = c(0, 800) ) MBCfilter <- tmixFilter("MBCfilter", c("FL1.H", "FL3.H"), K = 2, B = 100) filter(rituximab2, MBCfilter %subset% rectGate) ## ----prior-------------------------------------------------------------------- set.seed(100) library(flowStats) prior <- flowClust2Prior(res2[[2]], kappa = 1, Nt = 5000) prior2 <- prior prior2$Mu0[1, ] <- rep(box(200, prior2$lambda), 2) prior2$Lambda0 <- prior2$Lambda0 / 2 pfit2 <- flowClust( rituximab2, varNames = c("FL1.H", "FL3.H"), K = 2, prior = prior2, usePrior = "yes" ) par(mfrow = c(1, 2)) plot(res2[[2]], data = rituximab2) plot(pfit2, data = rituximab2)