In MassDynamics/lfq_processing: Processes Proteomics Files for Quantification.

knitr::opts_chunk$set(fig.cap = NULL, fig.path = params$output_figure)

library(knitr)
library(data.table)
library(ggplot2)
library(ggrepel)
library(GGally)
library(umap)
library(FactoMineR)
library(factoextra)
library(corrplot)
library(viridis)
library(ggpubr)
library(Hmisc)
library(plotly)
library(stringr)
library(bit64)

#assert that all the stuff we need is there. 
stopifnot(exists("expdes"))
stopifnot(exists("prot"))
stopifnot(exists("prot_int"))

expdes <- expdes[,c("condition", "experiment", "reporter_channel", "replicate")]

cvdt <- prot_int[Imputed == 0][, countRep := .N, by = .(id, condition)]
cvdt[, countRepMax := max(countRep), by = .(id, condition)]
cvdt[, ReplicatePC := countRep/countRepMax]
cvdt[, intensity := as.double(intensity)]
cvdt <- cvdt[ReplicatePC >= 0.5, .(cv = sd(intensity)/mean(intensity)), by = .(id, condition)]

p <- ggplot(cvdt, aes(x=cv, fill=condition, colour=condition)) +
  geom_density(alpha=0.4) +
  theme_minimal() +
  scale_x_continuous("% CV", labels = scales::percent) +
  ggtitle("Proteins - Reporter intensity CV")


ggplotly(p) %>% config(displayModeBar = T, 
                        modeBarButtons = list(list('toImage')),
                        displaylogo = F)