## ----knitr-opts, echo = FALSE, message = FALSE, cache = FALSE----------------- library(knitr) opts_chunk$set(cache = FALSE, echo = TRUE, message = FALSE, warning = FALSE, fig.width = 7, fig.height = 9, dpi = 100, fig.align = "center") ## ----netrc_req, echo = FALSE-------------------------------------------------- # This chunk is only useful for BioConductor checks and shouldn't affect any other setup if (!any(file.exists("~/.netrc", "~/_netrc"))) { labkey.netrc.file <- ImmuneSpaceR:::.get_env_netrc() labkey.url.base <- ImmuneSpaceR:::.get_env_url() } ## ----libraries, cache=FALSE--------------------------------------------------- library(ImmuneSpaceR) library(ggplot2) library(data.table) ## ----connection--------------------------------------------------------------- study <- CreateConnection(c("SDY180")) dt_fcs <- study$getDataset("fcs_analyzed_result") ## ----data-subset-------------------------------------------------------------- dt_fcs19 <- dt_fcs[population_name_reported %like% "Plasma"] dt_fcs19 <- dt_fcs19[, cohort := gsub("Study g", "G", cohort), ] ## ----data-summary------------------------------------------------------------- dt_fcs19_median <- dt_fcs19[, .(median_cell_reported = median(as.double(population_cell_number) + 1, na.rm = TRUE)), by = .(cohort,study_time_collected, population_name_reported)] ## ---- dev='png'--------------------------------------------------------------- ggplot(dt_fcs19, aes(x = as.factor(study_time_collected), y = as.double(population_cell_number) + 1)) + geom_boxplot() + geom_jitter() + scale_y_log10() + facet_grid(cohort~population_name_reported, scale = "free") + xlab("Time") + ylab(expression(paste("Number of cells/", mu, "l"))) + geom_line(data = dt_fcs19_median, aes(x = as.factor(study_time_collected), y = as.double(median_cell_reported), group = 1), color = "black", size = 1.2) + labs(title = "Plasma cell abundance after vaccination") + theme_IS()