## ----launch wpm, eval = FALSE------------------------------------------------- # library(wpm) # wpm() ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(data.frame("Sample" = c("s1","s2","s3","s4"))) ## ----echo=FALSE--------------------------------------------------------------- knitr::kable( data.frame("Sample" = c("s1","s2","s3","s4"), "Type" = c("A","A","B","C"), "Treatment" = c("trt1","tr1","Ctrl","Ctrl")) ) ## ----convert CSV file, eval = FALSE------------------------------------------- # imported_csv <- wpm::convertCSV("path-to-CSV-file") ## ----create an MSnSet object-------------------------------------------------- sample_names <- c("s1","s2","s3","s4", "s5") M <- matrix(NA, nrow = 4, ncol = 5) colnames(M) <- sample_names rownames(M) <- paste0("id", LETTERS[1:4]) pd <- data.frame(Environment = rep_len(LETTERS[1:3], 5), Category = rep_len(1:2, 5), row.names = sample_names) rownames(pd) <- colnames(M) my_MSnSet_object <- MSnbase::MSnSet(exprs = M,pData = pd) ## ----convert ESet/MSnSet object----------------------------------------------- df <- wpm::convertESet(my_MSnSet_object, "Environment") ## ----convert SummarizedExperiment object-------------------------------------- nrows <- 200 ncols <- 6 counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows) colData <- data.frame(Treatment=rep(c("ChIP", "Input"), 3), row.names=LETTERS[1:6]) se <- SummarizedExperiment::SummarizedExperiment(assays=list(counts=counts), colData=colData) df <- wpm::convertSE(se, "Treatment") ## ----run wpm with a CSV file, eval=FALSE-------------------------------------- # wpm_result <- wpm::wrapperWPM(user_df = imported_csv$df_wpm, # plate_dims = list(8,12), # nb_plates = 1, # forbidden_wells = "A1,A2,A3", # fixed_wells = "B1,B2", # spatial_constraint = "NS") ## ----run wpm------------------------------------------------------------------ wpm_result <- wpm::wrapperWPM(user_df = df, plate_dims = list(8,12), nb_plates = 1, forbidden_wells = "A1,A2,A3", fixed_wells = "B1,B2", spatial_constraint = "NS") ## ----visualize plate map------------------------------------------------------ drawned_map <- wpm::drawMap(df = wpm_result, sample_gps = length(levels(as.factor(colData$Treatment))), gp_levels = gp_lvl <- levels(as.factor(colData$Treatment)), plate_lines = 8, plate_cols = 12, project_title = "my Project Title") ## ----see the map-------------------------------------------------------------- drawned_map ## ----save map plot, eval=FALSE------------------------------------------------ # ggplot2::ggsave( # filename = "my file name", # plot = drawned_map, # width = 10, # height = 7, # units = "in" # ) ## ----eval = FALSE------------------------------------------------------------- # numberOfThePlate <- 1 # drawned_map <- wpm::drawMap(df = wpm_result[[numberOfThePlate]], # sample_gps = length(levels(as.factor(pd$Environment))), # gp_levels = gp_lvl <- levels(as.factor(pd$Environment)), # plate_lines = 8, # plate_cols = 12, # project_title = "my Project Title") ## ----SessionInfo-------------------------------------------------------------- sessionInfo()