diff --git a/src/.docker_modules/r-docher-test/1.0/Dockerfile b/src/.docker_modules/r-docher-test/1.0/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..9c3fa5cf773c6b44ed8f61a56acc5924df3edfcd
--- /dev/null
+++ b/src/.docker_modules/r-docher-test/1.0/Dockerfile
@@ -0,0 +1,9 @@
+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
diff --git a/src/.docker_modules/r-docher-test/1.0/install_pkgs.R b/src/.docker_modules/r-docher-test/1.0/install_pkgs.R
new file mode 100644
index 0000000000000000000000000000000000000000..20def570d4eea82c9488e92f888efacef4a94f6b
--- /dev/null
+++ b/src/.docker_modules/r-docher-test/1.0/install_pkgs.R
@@ -0,0 +1,6 @@
+#!/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
diff --git a/src/.docker_modules/r-docher-test/1.0/start_positions_individuals_2.R b/src/.docker_modules/r-docher-test/1.0/start_positions_individuals_2.R
new file mode 100755
index 0000000000000000000000000000000000000000..0ba0f18208c4c186d152aad9bb2add79a41ace12
--- /dev/null
+++ b/src/.docker_modules/r-docher-test/1.0/start_positions_individuals_2.R
@@ -0,0 +1,202 @@
+#!/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)