## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, # fig.align = "center", comment = ">" ) ## ---- eval = FALSE------------------------------------------------------------ # # install.packages("BiocManager") # BiocManager::install("POMA") ## ---- warning = FALSE, message = FALSE, comment = FALSE----------------------- library(POMA) library(MSnbase) library(ggplot2) library(patchwork) ## ---- warning = FALSE--------------------------------------------------------- # load example data data("st000336") # imputation using the default method KNN example_data <- st000336 %>% PomaImpute() example_data ## ---- warning = FALSE--------------------------------------------------------- none <- PomaNorm(example_data, method = "none") auto_scaling <- PomaNorm(example_data, method = "auto_scaling") level_scaling <- PomaNorm(example_data, method = "level_scaling") log_scaling <- PomaNorm(example_data, method = "log_scaling") log_transformation <- PomaNorm(example_data, method = "log_transformation") vast_scaling <- PomaNorm(example_data, method = "vast_scaling") log_pareto <- PomaNorm(example_data, method = "log_pareto") ## ---- warning = FALSE--------------------------------------------------------- dim(MSnbase::exprs(none)) dim(MSnbase::exprs(auto_scaling)) dim(MSnbase::exprs(level_scaling)) dim(MSnbase::exprs(log_scaling)) dim(MSnbase::exprs(log_transformation)) dim(MSnbase::exprs(vast_scaling)) dim(MSnbase::exprs(log_pareto)) ## ---- message = FALSE, comment = FALSE, warning = FALSE----------------------- a <- PomaBoxplots(none, group = "samples", jitter = FALSE) + ggtitle("Not Normalized") b <- PomaBoxplots(auto_scaling, group = "samples", jitter = FALSE) + ggtitle("Auto Scaling") + theme(axis.text.x = element_blank(), legend.position = "none") c <- PomaBoxplots(level_scaling, group = "samples", jitter = FALSE) + ggtitle("Level Scaling") + theme(axis.text.x = element_blank(), legend.position = "none") d <- PomaBoxplots(log_scaling, group = "samples", jitter = FALSE) + ggtitle("Log Scaling") + theme(axis.text.x = element_blank(), legend.position = "none") e <- PomaBoxplots(log_transformation, group = "samples", jitter = FALSE) + ggtitle("Log Transformation") + theme(axis.text.x = element_blank(), legend.position = "none") f <- PomaBoxplots(vast_scaling, group = "samples", jitter = FALSE) + ggtitle("Vast Scaling") + theme(axis.text.x = element_blank(), legend.position = "none") g <- PomaBoxplots(log_pareto, group = "samples", jitter = FALSE) + ggtitle("Log Pareto") + theme(axis.text.x = element_blank(), legend.position = "none") a (b + c + d) / (e + f + g) ## ---- message = FALSE, comment = FALSE, warning = FALSE----------------------- h <- PomaDensity(none, group = "features") + ggtitle("Not Normalized") i <- PomaDensity(auto_scaling, group = "features") + ggtitle("Auto Scaling") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) j <- PomaDensity(level_scaling, group = "features") + ggtitle("Level Scaling") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) k <- PomaDensity(log_scaling, group = "features") + ggtitle("Log Scaling") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) l <- PomaDensity(log_transformation, group = "features") + ggtitle("Log Transformation") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) m <- PomaDensity(vast_scaling, group = "features") + ggtitle("Vast Scaling") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) n <- PomaDensity(log_pareto, group = "features") + ggtitle("Log Pareto") + theme(axis.title.x = element_blank(), axis.title.y = element_blank()) h (i + j + k) / (l + m + n) ## ----------------------------------------------------------------------------- sessionInfo()