## ----knitr, echo = FALSE------------------------------------------------------ library(knitr) opts_chunk$set(message = FALSE, fig.align = "center", fig.width = 7, fig.height = 7) ## ----netrc_req, echo = FALSE-------------------------------------------------- # This chunk is only useful for BioConductor checks and shouldn't affect any other setup if (!any(file.exists("~/.netrc", "~/_netrc"))) { labkey.netrc.file <- ImmuneSpaceR:::.get_env_netrc() labkey.url.base <- ImmuneSpaceR:::.get_env_url() } ## ----------------------------------------------------------------------------- library(ImmuneSpaceR) library(data.table) library(ggplot2) con <- CreateConnection("SDY144") ## ----------------------------------------------------------------------------- flow <- con$getDataset("fcs_analyzed_result") hai <- con$getDataset("hai") vn <- con$getDataset("neut_ab_titer") ## ----subset------------------------------------------------------------------- pb <- flow[population_name_reported %in% c("Plasma cells,Freq. of,B lym CD27+", "Plasmablast,Freq. of,Q3: CD19+, CD20-")] pb <- pb[, population_cell_number := as.numeric(population_cell_number)] pb <- pb[study_time_collected == 7 & study_time_collected_unit == "Days"] # 13 subjects pb <- pb[, list(participant_id, population_cell_number, population_name_reported)] ## ----FC----------------------------------------------------------------------- # HAI hai <- hai[, response := value_preferred / value_preferred[study_time_collected == 0], by = "virus,cohort,participant_id"][study_time_collected == 30] hai <- hai[, list(participant_id, virus, response)] dat_hai <- merge(hai, pb, by = "participant_id", allow.cartesian = TRUE) # VN vn <- vn[, response:= value_preferred/value_preferred[study_time_collected == 0], by = "virus,cohort,participant_id"][study_time_collected == 30] vn <- vn[, list(participant_id, virus, response)] dat_vn <- merge(vn, pb, by = "participant_id", allow.cartesian = TRUE) ## ----HAI, dev='png'----------------------------------------------------------- ggplot(dat_hai, aes(x = population_cell_number, y = response)) + geom_point() + geom_smooth(method = "lm") + facet_grid(virus ~ population_name_reported, scale = "free") + xlab("Number of cells") + ylab("HI fold-increase Day 30 vs. baseline") + theme_IS() ## ----VN, dev='png'------------------------------------------------------------ ggplot(dat_vn, aes(x = population_cell_number, y = response)) + geom_point() + geom_smooth(method = "lm") + facet_grid(virus ~ population_name_reported, scale = "free") + xlab("Number of cells") + ylab("VN fold-increase Day 30 vs. baseline") + theme_IS()