## ---- echo = FALSE, message=FALSE---------------------------------------- knitr::opts_chunk$set(collapse = TRUE, comment = "#>", tidy = TRUE) library(flowCore) library(flowTime) library(ggplot2) ## ------------------------------------------------------------------------ plate1<-read.flowSet(path=system.file("extdata", "ss_example", package = "flowTime"), alter.names = TRUE) # add plate numbers to the sampleNames sampleNames(plate1)<-paste("1_", sampleNames(plate1), sep = "") dat<-plate1 ## ---- eval = F----------------------------------------------------------- # plate2 <- read.flowSet(path = paste(experiment, "_2/", sep = ""), # alter.names = TRUE) # sampleNames(plate2) <- paste("2_", sampleNames(plate2), sep = "") # dat <- rbind2(plate1, plate2) ## ------------------------------------------------------------------------ annotation <- read.csv(system.file("extdata", "ss_example.csv", package = "flowTime")) head(annotation) sampleNames(dat) sampleNames(dat) == annotation$name ## ---- eval = F----------------------------------------------------------- # annotation <- cbind(annotation, 'name' = sampleNames(dat)) # # or # annotation <- createAnnotation(yourFlowSet = dat) # write.csv(annotation, file = 'path/to/yourAnnotation.csv') ## ------------------------------------------------------------------------ adat <- annotateFlowSet(yourFlowSet = dat, annotation_df = annotation, mergeBy = 'name') head(rownames(pData(adat))) head(pData(adat)) ## ---- eval = F----------------------------------------------------------- # write.flowSet(adat, outdir = 'your/favorite/directory') # # # Read the flowSet with the saved experimental meta data # read.flowSet('flowSet folder', path = 'your/flow/directory', # phenoData = 'annotation.txt', alter.names = TRUE) ## ---- fig.width = 4, fig.height = 4-------------------------------------- loadGates() # use the default included gateSet dat.SS <- steadyState(flowset = adat, ploidy = 'diploid', only = 'singlets') p <- ggplot(dat.SS, aes(x = as.factor(treatment), y = FL2.A, fill = AFB)) + geom_boxplot(outlier.size = NA) + facet_grid(IAA~AFB) + theme_classic(base_family = 'Arial', base_size = 16) + ylim(c(-1000,10000)) + xlab(expression(paste('Auxin (',mu,'M)',sep = ""))) + ylab('Fluorescence (AU)') + theme(legend.position="none") p