## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(Cleanet) library(readr) library(dplyr) library(ggplot2) ## ----read_data---------------------------------------------------------------- path <- system.file("extdata", "df_mdipa.csv", package="Cleanet") df_mdipa <- read_csv(path, col_types=cols()) print(df_mdipa) ## ----cleanet_basic------------------------------------------------------------ cols <- c("CD45", "CD123", "CD19", "CD11c", "CD16", "CD56", "CD294", "CD14", "CD3", "CD20", "CD66b", "CD38", "HLA-DR", "CD45RA", "DNA1", "DNA2") cleanet_res <- cleanet(df_mdipa, cols, cofactor=5) ## ----cleanet_basic_status----------------------------------------------------- print(table(cleanet_res$status)) ## ----cleanet_basic_sensitivity------------------------------------------------ print(cleanet_res$sensitivity) ## ----bivariate_basic---------------------------------------------------------- ggplot(df_mdipa, aes(x=asinh(DNA1/5), y=asinh(CD45/5), color=cleanet_res$status)) + geom_point(size=0.2) + scale_color_discrete(name="Status") + theme_bw() ## ----debris_default----------------------------------------------------------- is_debris <- filter_debris_cytof(df_mdipa, cols) ## ----debris_custom------------------------------------------------------------ is_debris <- filter_debris_cytof(df_mdipa, cols, threshold = 0.35) ## ----cleanet_filtered--------------------------------------------------------- cleanet_res <- cleanet(df_mdipa, cols, cofactor=5, is_debris=is_debris) print(cleanet_res$sensitivity) ggplot(df_mdipa, aes(x=asinh(DNA1/5), y=asinh(CD45/5), color=cleanet_res$status)) + geom_point(size=0.2) + scale_color_discrete(name="Status") + theme_bw() ## ----CD294-------------------------------------------------------------------- ggplot(df_mdipa, aes(x=asinh(DNA1/5), y=asinh(CD45/5), color=asinh(CD294/5))) + geom_point(size=0.2) + scale_color_gradient(low="black", high="red") + theme_bw() ## ----label-------------------------------------------------------------------- print(table(df_mdipa$label)) ## ----classify_doublets-------------------------------------------------------- singlet_clas <- df_mdipa$label[which(cleanet_res$status!="Doublet")] doublet_clas <- classify_doublets(cleanet_res, singlet_clas) sort(table(doublet_clas)) ## ----compare------------------------------------------------------------------ df_exp_obs <- compare_doublets_exp_obs(doublet_clas, singlet_clas, cleanet_res) arrange(df_exp_obs, -Expected) ## ----compare_plot------------------------------------------------------------- ggplot(df_exp_obs, aes(x=Expected, y=Observed)) + geom_point() + geom_abline(slope=1, yintercept=0, linetype="dotted") + theme_bw()