## ----include = FALSE---------------------------------------------------------- Sys.setenv(R_USER_LIBS = tempdir()) #Just in case for CRAN library(biodosetools) knitr::opts_chunk$set( fig.dpi = 96, collapse = TRUE, comment = "#>" ) ## ----sc-interlab-01, echo=FALSE, out.width='100%', fig.align='center', fig.cap="'Data Input' box and 'Results' tabbed box in the interlaboratory comparison module when loading curves from an `.rds` file for two laboratories."---- knitr::include_graphics("figures/screenshot-interlab-01.png") ## ----load-interlab-data, tidy=TRUE, tidy.opts=list(width.cutoff=60)----------- fit_results_A1 <- system.file("extdata", "A1_Estimation_results.rds", package = "biodosetools") %>% readRDS() fit_results_A2 <- system.file("extdata", "A2_Estimation_results.rds", package = "biodosetools") %>% readRDS() ## ----interlab-data------------------------------------------------------------ list_lab_names <- list("A1", "A2") all_rds <- list(fit_results_A1, fit_results_A2) tables_list <- summary_curve_tables( num_labs = 2, list_lab_names, all_rds ) ## ----summary_plots------------------------------------------------------------ yield_boxplot( dat = tables_list[[1]], place = "UI" ) dose_boxplot( dat = tables_list[[1]], place = "UI" ) u_test_plot( dat = tables_list[[1]], place = "UI" ) DI_plot( dat = tables_list[[1]], place = "UI" ) ## ----curve-plots-------------------------------------------------------------- curves_plot( dat = tables_list[[2]], curve = "manual", curve_type = "lin_quad", place = "UI" ) bar_plots( dat = tables_list[[2]], curve = "manual", place = "UI" ) ## ----sc-interlab-04, echo=FALSE, out.width='100%', fig.align='center', fig.cap="'Z-score Data input options' in the interlaboratory comparison module."---- knitr::include_graphics("figures/screenshot-interlab-04.png") ## ----sc-interlab-05, echo=FALSE, out.width='100%', fig.align='center', fig.cap="'Z-score Results table' in the interlaboratory comparison module."---- knitr::include_graphics("figures/screenshot-interlab-05.png") ## ----interlab-zscore---------------------------------------------------------- zscore_S1 <- calc.zValue.new( X = tables_list[[1]][["estimate"]][1:2], type = "dose", alg = "algA", c = 2.56 ) zscore_S2 <- calc.zValue.new( X = tables_list[[1]][["estimate"]][3:4], type = "dose", alg = "algA", c = 3.41 ) zscore_S3 <- calc.zValue.new( X = tables_list[[1]][["estimate"]][5:6], type = "dose", alg = "algA", c = 4.54 ) ## ----plots-interlab-zscore---------------------------------------------------- data_frame_zscore <- data.frame( Lab = tables_list[[1]][["Lab"]], Sample = tables_list[[1]][["Sample"]], Type = tables_list[[1]][["Type"]], Reference = c(2.56, 3.41, 4.54), Dose = tables_list[[1]][["estimate"]], Deviation = tables_list[[1]][["estimate"]] - c(2.56, 3.41, 4.54), Zscore = c(zscore_S1, zscore_S2, zscore_S3), stringsAsFactors = FALSE ) plot_1 <- plot_zscore_all( zscore = data_frame_zscore, select_method = "algA", place = "UI" ) plot_2 <- plot_deviation_all( zscore = data_frame_zscore, select_method = "algA", place = "UI" ) plot_3 <- plot_interlab_v2( zscore = data_frame_zscore, select_method = "algA", sum_table = tables_list[[1]], place = "UI" ) plot_4 <- plot_interlab_deviation( zscore = data_frame_zscore, sum_table = tables_list[[1]], place = "UI" ) line_triage <- list(`1` = 2.56, `2` = 3.41, `3` = 4.54) plot_5 <- plot_triage_interlab( line_triage, sum_table = tables_list[[1]], place = "UI" ) ## ----all-plots, fig.width=6, fig.height=3.5, fig.align='center', fig.cap="Plots generated by \\{biodosetools\\}."---- plot_1 plot_2 for (p in plot_3) print(p) for (p in plot_4) print(p) for (p in plot_5) print(p)