## ----knitr-opts, echo = FALSE, message = FALSE, cache = FALSE----------------- library(knitr) opts_chunk$set(cache = FALSE, echo = TRUE, message = FALSE, warning = FALSE, fig.width = 7, fig.height = 4, dpi = 100, fig.align = "center") ## ----netrc_req, echo = FALSE-------------------------------------------------- # This chunk is only useful for BioConductor checks and shouldn't affect any other setup if (!any(file.exists("~/.netrc", "~/_netrc"))) { labkey.netrc.file <- ImmuneSpaceR:::.get_env_netrc() labkey.url.base <- ImmuneSpaceR:::.get_env_url() } ## ----libraries, cache=FALSE--------------------------------------------------- library(ImmuneSpaceR) library(ggplot2) library(data.table) ## ----connection--------------------------------------------------------------- study <- CreateConnection("SDY269") dt_hai <- study$getDataset("hai", reload = TRUE) dt_fcs <- study$getDataset("fcs_analyzed_result", reload = TRUE) dt_elispot <- study$getDataset("elispot", reload = TRUE) ## ----data-subset-------------------------------------------------------------- # Compute max fold change for HAI, and remove time zero dt_hai <- dt_hai[, hai_response := value_preferred / value_preferred[study_time_collected == 0], by = "virus,cohort,participant_id"][study_time_collected == 28] dt_hai <- dt_hai[, list(hai_response = max(hai_response)), by = "cohort,participant_id"] # Define variable for ELISPOT, keep only the IgG class dt_elispot <- dt_elispot[, elispot_response := spot_number_reported + 1][study_time_collected == 7 & analyte == "IgG"] # Compute % plasmablasts dt_fcs <- dt_fcs[, fcs_response := (as.double(population_cell_number) + 1) / as.double(base_parent_population)][study_time_collected == 7] ## ----merging------------------------------------------------------------------ # Let's key the different datasets setkeyv(dt_hai, c("participant_id")) setkeyv(dt_fcs, c("participant_id")) setkeyv(dt_elispot, c("participant_id")) dt_all <- dt_hai[dt_fcs, nomatch = 0][dt_elispot, nomatch = 0] ## ----plot1, dev='png'--------------------------------------------------------- ggplot(dt_all, aes(x = as.double(fcs_response), y = elispot_response, color = cohort)) + geom_point() + scale_y_log10() + scale_x_log10() + geom_smooth(method = "lm") + xlab("Total plasmablasts (%)") + ylab("Influenza specific cells\n (per 10^6 PBMCs)") + theme_IS() ## ----plot2, dev='png'--------------------------------------------------------- ggplot(dt_all, aes(x = as.double(hai_response), y = elispot_response, color = cohort)) + geom_point() + scale_x_continuous(trans = "log2") + scale_y_log10() + geom_smooth(method = "lm") + xlab("HAI fold") + ylab("Influenza specific cells\n (per 10^6 PBMCs)") + theme_IS()