## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) ## ----metaformat1, echo = FALSE, results = 'asis'------------------------------ library(knitr) df <- data.frame( Filenam = c("p1_a12.fcs", "p2_d08.fcs", "p3_g1.fcs"), #should be the same as the GUID in the FCS files Plate = c("Plate1", "Plate2", "Plate3"), Well = c("A12", "D08", "G01"), Column = c("Col.12", "Col.08", "Col.01"), Row = c("Row.01", "Row.04", "Row.07"), Well.lab = c("P1_A12", "P2_D08", "P3_G01")) kable(df) ## ----metaformat2, echo = FALSE, results = 'asis'------------------------------ library(knitr) df <- data.frame( Filenam = c("090122.fcs", "070122.fcs", "010122.fcs"), #should be the same as the GUID in the FCS files Batch = c("Batch1", "Batch2", "Batch3")) kable(df) ## ----install_mapfx, eval=FALSE------------------------------------------------ # if (!require("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("MAPFX") ## ----dependency--------------------------------------------------------------- library(MAPFX) ## specify the package names suppressPackageStartupMessages({ library(flowCore) library(Biobase) library(stringr) library(uwot) library(iCellR) library(igraph) library(ggplot2) library(RColorBrewer) library(Rfast) library(ComplexHeatmap) library(circlize) library(glmnetUtils) library(e1071) library(xgboost) library(parallel) library(pbapply) library(reshape2) library(gtools) library(utils) library(stats) library(cowplot) }) ## ----MapfxMPC_impu_example, eval=TRUE----------------------------------------- # import built-in data data(ord.fcs.raw.meta.df.out_mpc) data(ord.fcs.raw.mt_mpc) # create an Output directory in the current working directory for the argument 'Outpath' of the MapfxMPC function dir.create(file.path(tempdir(), "MPC_impu_Output")) # usage # when impute = TRUE, randomly selecting 50% of the cells in each well for model training set.seed(123) MapfxMPC_impu_obj <- MapfxMPC( runVignette = TRUE, #set FALSE if not running this Vignette runVignette_meta = ord.fcs.raw.meta.df.out_mpc, #set NULL if not running this Vignette runVignette_rawInten = ord.fcs.raw.mt_mpc, #set NULL if not running this Vignette FCSpath = NULL, # users specify their own input path Outpath = file.path(tempdir(), "MPC_impu_Output"), # or users specify their own output path file_meta = "auto", bkb.v = c( "FSC-H", "FSC-W", "SSC-H", "SSC-W", "CD69-CD301b", "MHCII", "CD4", "CD44", "CD8", "CD11c", "CD11b", "F480", "Ly6C", "Lineage", "CD45a488", "CD24", "CD103"), yvar = "Legend", control.wells = c( "P1_A01", "P2_A01", "P3_A01", "P3_F04", "P3_F05", "P3_F06", "P3_F07", "P3_F08", "P3_F09", "P3_F10", "P3_F11", "P3_F12", "P3_G01", "P3_G02"), bkb.upper.quantile = 0.9, bkb.lower.quantile = 0.1, bkb.min.quantile = 0.01, inf.lower.quantile = 0.1, inf.min.quantile = 0.01, plots.bkc.bkb = TRUE, plots.bkc.inf = TRUE, plots.initM = TRUE, plots.rmWellEffect = TRUE, impute = TRUE, models.use = c("XGBoost"), extra_args_regression_params = list(list(nrounds = 1500, eta = 0.03)), prediction_events_downsampling = NULL, impu.training = FALSE, plots.imputation = TRUE, cluster.analysis.bkb = TRUE, plots.cluster.analysis.bkb = TRUE, cluster.analysis.all = TRUE, plots.cluster.analysis.all = TRUE, cores = 4L) # check the details help(MapfxMPC, package = "MAPFX") ## ----mapfxNorm_MPC, eval=FALSE------------------------------------------------ # # import built-in data # data(ord.fcs.raw.meta.df.out_mpc) # data(ord.fcs.raw.mt_mpc) # # # create an Output directory in the current working directory for the argument 'Outpath' of the MapfxMPC function # dir.create(file.path(tempdir(), "MPC_NOimpu_Output")) # # # usage # MapfxMPC_NOimpu_obj <- MapfxMPC( # runVignette = TRUE, #set FALSE if not running this Vignette # runVignette_meta = ord.fcs.raw.meta.df.out_mpc, #set NULL if not running this Vignette # runVignette_rawInten = ord.fcs.raw.mt_mpc, #set NULL if not running this Vignette # FCSpath = NULL, # users specify their own input path # Outpath = file.path(tempdir(), "MPC_NOimpu_Output"), # or users specify their own output path # file_meta="auto", # bkb.v = c( # "FSC-H", "FSC-W", "SSC-H", "SSC-W", "CD69-CD301b", "MHCII", # "CD4", "CD44", "CD8", "CD11c", "CD11b", "F480", # "Ly6C", "Lineage", "CD45a488", "CD24", "CD103"), # yvar="Legend", # control.wells = c( # "P1_A01", "P2_A01", "P3_A01", # "P3_F04", "P3_F05", "P3_F06", "P3_F07", "P3_F08", # "P3_F09", "P3_F10", "P3_F11", "P3_F12", # "P3_G01", "P3_G02"), # bkb.upper.quantile = 0.9, # bkb.lower.quantile = 0.1, # bkb.min.quantile = 0.01, # inf.lower.quantile = 0.1, # inf.min.quantile = 0.01, # plots.bkc.bkb = TRUE, plots.bkc.inf = TRUE, # plots.initM = TRUE, # plots.rmWellEffect = TRUE, # impute = FALSE, # cluster.analysis.bkb = TRUE, plots.cluster.analysis.bkb = TRUE, # cores = 4L) # # # check the details # help(MapfxMPC, package = "MAPFX") ## ----mapfxNorm_FFC, eval=TRUE------------------------------------------------- # import built-in data data(ord.fcs.raw.meta.df.out_ffc) data(ord.fcs.raw.mt_ffc) # create an Output directory in the current working directory for the argument 'Outpath' of the MapfxFFC function dir.create(file.path(tempdir(), "FFCnorm_Output")) MapfxFFC_obj <- MapfxFFC( runVignette = TRUE, #set FALSE if not running this Vignette runVignette_meta = ord.fcs.raw.meta.df.out_ffc, #set NULL if not running this Vignette runVignette_rawInten = ord.fcs.raw.mt_ffc, #set NULL if not running this Vignette FCSpath = NULL, # users specify their own input path Outpath = file.path(tempdir(), "FFCnorm_Output"), # or users specify their own output path protein.v = c("CD3","CD4","CD8","CD45"), protein.upper.quantile = 0.9, protein.lower.quantile = 0.1, protein.min.quantile = 0.01, plots.bkc.protein = TRUE, plots.initM = TRUE, plots.rmBatchEffect = TRUE, cluster.analysis.protein = TRUE, plots.cluster.analysis.protein = TRUE) # check the details help(MapfxFFC, package = "MAPFX") ## ----sessinfo----------------------------------------------------------------- sessionInfo()