remove r-docker-test docker_module

src/.docker_modules/r-docher-test/1.0/Dockerfile

-FROM rocker/r-base:4.2.3
-
-## copy Rscript files
-COPY ./*.R .
-
-RUN Rscript install_pkgs.R
-
-# command to run on container start
-CMD [ "bash" ]
\ No newline at end of file

src/.docker_modules/r-docher-test/1.0/install_pkgs.R

-#!/bin/Rscript
-# Packages installation:
-list.of.packages <- c("BiocManager", "ggplot2", "dplyr", "reshape2", 
-                      "RColorBrewer", "R.utils")
-new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
-if(length(new.packages)) install.packages(new.packages, dependencies = T)
\ No newline at end of file

src/.docker_modules/r-docher-test/1.0/start_positions_individuals_2.R

-#!/bin/Rscript
-library(dplyr)
-library(ggplot2)
-library(tidyverse)
-library(RColorBrewer)
-library(conflicted)
-#résolution de conflits entre les bibliothèques dplyr et stats
-conflict_prefer("filter", "dplyr")
-conflict_prefer("lag", "dplyr")
-
-# Load Start_positions_count files:
-
-list_file <- list.files(path=".", 
-                        pattern="*.txt", 
-                        all.files=FALSE, 
-                        full.names=FALSE)
-file_to_load <- paste0("./", list_file[1])
-filename <- strsplit(list_file[1], split = "[.]")[[1]][1]
-
-sam_bc01 <- read.table(file_to_load, header = F)
-sam_bc01[3] <- rep(filename, length(sam_bc01[,1]))
-
-# Function to parse and arrange data:
-
-parsingData <- function(df) {
-  binsize <- 10
-  pos <- as.data.frame(table(df[,2]))
-  colnames(pos)[1] <- "Start"
-  
-  Start <- as.data.frame(as.factor(seq(0, 3300)))
-  colnames(Start)[1] = "Start"
-  
-  tmp <- dplyr::left_join(Start, pos)
-  tmp[is.na(tmp)] <- 0
-  
-  tmp$Start <- as.numeric(tmp$Start)
-  
-  df2 <- as_tibble(tmp) %>% 
-    mutate(bin = round(Start/binsize)*binsize) %>% 
-    group_by(bin) %>% 
-    summarize(nb_reads = sum(Freq, na.rm = T))
-  df2[is.na(df2)] <- 0
-  df2[3] <- rep(df[1,3], length(df2$bin))
-  colnames(df2) <- c("Start_position", "nb_reads", "Barcode")
-  df2
-}
-
-df_parsed <- parsingData(sam_bc01)
-
-ggplot(df_parsed, aes(Start_position, nb_reads)) + 
-  geom_area(alpha = 0.5, fill = "blue") + 
-  scale_y_sqrt() +
-  facet_wrap(facets = vars(df_parsed$Barcode)) +
-  theme_light()+
-  scale_x_continuous(breaks = c(0, 127, 1114, 1490, 2554, 2732, 2907, 3421),
-                     label = c("1692", "1819", "2806", "EcoRI", "1065", 
-                               "1243", "1418", "1932")) + 
-  theme(axis.text.x = element_text(angle = 45)
-  )
-
-ggsave(paste0(filename,".jpg"),
-       plot = last_plot(),
-       scale = 2,
-       width = 1920,
-       height = 1080,
-       units = "px",
-       dpi = 300,
-)
-
-# Classify reads based on start-position:
-
-# Separate preCore & pg:
-classify_reads <- function(read_info) {
-  if (read_info <= 103) {
-    promoter <- "preCore"
-  }
-  else if (read_info >= 117 &
-           read_info <= 276) {
-    promoter <- "pgRNA"
-  }
-  else if (read_info >= 1106 & 
-           read_info <= 1221 ) {
-    promoter <- "preS1"
-  }
-  else if (read_info >= 1455 & 
-           read_info <= 1632 ) {
-    promoter <- "preS2/S"
-  }
-  else if (read_info >= 2550 & 
-           read_info <= 2968 ) {
-    promoter <- "HBx"
-  }
-  else promoter <- "Undefined"
-}
-
-colnames(sam_bc01) <- c("read_ID", "start_position", "barcode")
-sam_bc01$promoter <- sapply(sam_bc01$start_position, 
-                            classify_reads)
-
-write.table(sam_bc01,
-            file = "classification_of_reads_per_RNA.txt",
-            quote = FALSE, 
-            sep = "\t", 
-            row.names = FALSE)
-
-# Compute Reads number per promoters:
-list_name_samples <- list(filename)
-
-count_promoter_reads <- function(barcode, df) {
-  tmpdf <- as.data.frame(df)
-  tmpdf <- tmpdf[tmpdf$Barcode == barcode,]
-  preCore <- sum(tmpdf$nb_reads[tmpdf$Start_position <= 103])
-  pgRNA <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 117 & 
-                                tmpdf$Start_position <= 276])
-  preS1 <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 1106 & 
-                                tmpdf$Start_position <= 1221])
-  preS2S <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 1455 & 
-                                 tmpdf$Start_position <= 1632])
-  HBx <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 2550 & 
-                              tmpdf$Start_position <= 2968])
-  total <- sum(preCore, pgRNA, preS1, preS2S, HBx)
-  res <- c(preCore/total*100, pgRNA/total*100, preS1/total*100, 
-           preS2S/total*100, HBx/total*100, total)
-  return(res)
-}
-
-abscount_promoter_reads <- function(barcode, df) {
-  tmpdf <- as.data.frame(df)
-  tmpdf <- tmpdf[tmpdf$Barcode == barcode,]
-  preCore <- sum(tmpdf$nb_reads[tmpdf$Start_position <= 103])
-  pgRNA <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 117 & 
-                                tmpdf$Start_position <= 276])
-  preS1 <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 1106 & 
-                                tmpdf$Start_position <= 1221])
-  preS2S <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 1455 & 
-                                 tmpdf$Start_position <= 1632])
-  HBx <- sum(tmpdf$nb_reads[tmpdf$Start_position >= 2550 & 
-                              tmpdf$Start_position <= 2968])
-  total <- sum(preCore, pgRNA, preS1, preS2S, HBx)
-  res <- c(preCore, pgRNA, preS1, preS2S, 
-           HBx, total)
-  return(res)
-}
-
-promoters <- factor(c("preCore", "pgRNA", "preS1", "preS2/S", "HBx"), 
-                    levels = c("preCore", "pgRNA", "preS1", "preS2/S", "HBx"))
-
-abs_count_reads <- data.frame()
-abs_count_reads <- sapply(list_name_samples, 
-                          abscount_promoter_reads, 
-                          df_parsed)
-abs_count_reads <- cbind(c(as.vector(promoters),"total"), abs_count_reads)
-colnames(abs_count_reads) <- c("promoter", "read_number")
-
-write.table(abs_count_reads,
-            file = "Count_reads_per_promoter.tsv",
-            quote = FALSE, 
-            sep = "\t", 
-            row.names = FALSE)
-
-resultats_start_promoters <- lapply(list_name_samples, 
-                                    count_promoter_reads, 
-                                    df_parsed)
-
-resultats_start_promoters <- as.data.frame(do.call(cbind, 
-                                                   resultats_start_promoters))
-totalCountSample <- as.data.frame(resultats_start_promoters[6,])
-colnames(totalCountSample) <- c(filename)
-resultats_start_promoters <- as.data.frame(resultats_start_promoters[1:5,])
-colnames(resultats_start_promoters) <- as.vector(list_name_samples)
-resultats_start_promoters <- cbind(promoters, resultats_start_promoters)
-formated_start_promoters <- pivot_longer(resultats_start_promoters, 
-                                         cols = c(filename),
-                                         names_to = "Barcodes", 
-                                         values_to = "nb_reads")
-
-mycolors <- colorRampPalette(brewer.pal(10, "Paired"))(10)
-mycolors5 <- c("#712E80", "#006695", "#3B9746", "#1F4F25", "#F5751A")
-mycolors6 <- c("#A6CEE3", "#3362ff", "#33c5ff", "#6A3D9A", "#d60000")
-
-plot_camembert <- function(barcode, df, tot) {
-  camembert <- ggplot(df[df$Barcodes == barcode,], aes(x = barcode, 
-                                                       y = nb_reads, 
-                                                       fill=promoters)) +
-    geom_col() +
-    coord_polar("y") +
-    scale_fill_manual(values = mycolors5) +
-    labs(title = paste0("#reads = ", tot[1,barcode]), x=element_blank(), y=element_blank()) +
-    theme_light()
-  
-  print(camembert)
-  
-  ggsave(filename = paste0("./Reads_start_promoters_", barcode, "_camembert.jpg"),
-         plot = last_plot(),
-         scale = 1,
-         width = 1920,
-         height = 1080,
-         units = "px",
-         dpi = 300)
-}
-
-lapply(list_name_samples, plot_camembert, formated_start_promoters, totalCountSample)