diff --git a/install_packages.log b/install_packages.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/src/.docker_modules/readthroughbincounts/0.1/Dockerfile b/src/.docker_modules/readthroughbincounts/0.1/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..94a215b80cca4d64fee4cf8891d77f662aae054d
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/Dockerfile
@@ -0,0 +1,28 @@
+FROM rocker/tidyverse:4.3.1
+LABEL AUTHOR="Xavier Grand"
+LABEL MAINTAINER="Xavier Grand <xavier.grand@inserm.fr>"
+LABEL EMAIL="<xavier.grand@ens-lyon.fr>"
+LABEL build_date="2023-10-23"
+
+RUN apt-get update \
+ && apt-get install -y --no-install-recommends \
+ libcurl4-openssl-dev \
+ libssl-dev \
+ libxml2-dev \
+ libharfbuzz-dev \
+ libfribidi-dev \
+ libmariadb-dev \
+ libbz2-dev \
+ procps
+
+## copy Rscript files
+
+COPY src/ src/
+COPY LICENSE .
+COPY README.md .
+
+## Install packages
+RUN Rscript src/install_packages.R 2> install_packages.log
+
+## Langage
+CMD ["bash"]
\ No newline at end of file
diff --git a/src/.docker_modules/readthroughbincounts/0.1/LICENSE b/src/.docker_modules/readthroughbincounts/0.1/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..4af7fc24ad11693e6dd4883ef60a19157df19033
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/LICENSE
@@ -0,0 +1,661 @@
+ GNU AFFERO GENERAL PUBLIC LICENSE
+ Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+ Preamble
+
+ The GNU Affero General Public License is a free, copyleft license for
+software and other kinds of works, specifically designed to ensure
+cooperation with the community in the case of network server software.
+
+ The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works. By contrast,
+our General Public Licenses are intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users.
+
+ When we speak of free software, we are referring to freedom, not
+price. Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
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+want it, that you can change the software or use pieces of it in new
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+
+ Developers that use our General Public Licenses protect your rights
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+you this License which gives you legal permission to copy, distribute
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+permissions. However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+ 15. Disclaimer of Warranty.
+
+ THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+ 16. Limitation of Liability.
+
+ IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+ 17. Interpretation of Sections 15 and 16.
+
+ If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+ END OF TERMS AND CONDITIONS
+
+ How to Apply These Terms to Your New Programs
+
+ If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+ To do so, attach the following notices to the program. It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+ ENS M1 ML
+ Copyright (C) 2022 LBMC / Hub / formations
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU Affero General Public License as published
+ by the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU Affero General Public License for more details.
+
+ You should have received a copy of the GNU Affero General Public License
+ along with this program. If not, see <https://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+ If your software can interact with users remotely through a computer
+network, you should also make sure that it provides a way for users to
+get its source. For example, if your program is a web application, its
+interface could display a "Source" link that leads users to an archive
+of the code. There are many ways you could offer source, and different
+solutions will be better for different programs; see section 13 for the
+specific requirements.
+
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU AGPL, see
+<https://www.gnu.org/licenses/>.
diff --git a/src/.docker_modules/readthroughbincounts/0.1/README.md b/src/.docker_modules/readthroughbincounts/0.1/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..4e2fbb0caf05089146e8e1b2f9ffa2277ed389cf
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/README.md
@@ -0,0 +1,227 @@
+# ReadthroughBinCounts
+
+Comptage des readthrough dans des fichiers BAM, à partir de coordonnées BED
+
+## Step 1 : GTF select 'gene' lines
+
+```
+grep -P "\tgene\t" Homo_sapiens.GRCh37.75.gtf > Homo_sapiens.GRCh37.75.genes.gtf
+```
+
+## Step 2 : bed pour avoir le gene puis le gene + 10kb
+
+Packages :
+- tidyverse
+- progress
+- GenomicRanges
+- valr
+- rtracklayer
+- optparse
+- foFuture
+- DESeq2
+- viridis
+- gplots
+- openxlsx
+
+
+```
+Rscript --vanilla ./src/refToKallisto.R --help
+Usage: ./src/refToKallisto.R [options]
+
+
+Options:
+ -f CHARACTER, --file=CHARACTER
+ GTF File
+
+ -o CHARACTER, --out=CHARACTER
+ output repertory [default= ./]
+
+ -s CHARACTER, --suffix=CHARACTER
+ A suffix to specify your results [default= readtrhough]
+
+ -r NUMBER, --RT=NUMBER
+ Size of Readthrough search zone after last gene exon (#bases) [default= 10000]
+
+ -c CHR, --chr=CHR
+ List of chromosomes you want to keep (default: human chr)
+ [default= 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,X,Y,MT]
+
+ -h, --help
+ Show this help message and exit
+
+
+Rscript --vanilla ./src/refToKallisto.R -f "./data/Homo_sapiens.GRCh37.75.genes.gtf" -o "./results/"
+
+Loading GTF file ( 1 / 6 )
+Export classical Bed file ( 2 / 6 )
+Create 10000kb extension ( 3 / 6 )
+Overlap on genes : coordinate correction ( 4 / 6 )
+ [==================================] 100% [Elapsed time: 00:00:18 || Estimated time remaining: 0s]
+Overlap on genes : Stranded correction ( 5 / 6 )
+ [==================================] 100% [Elapsed time: 00:01:15 || Estimated time remaining: 0s]
+Export Extension Bed file ( 6 / 6 )
+
+```
+/!\ faire sur le dernier exon et non tout le gène, reprendre data Xavier
+Version - last exon ( All bases )
+
+
+## Step 3 : création d'un fasta file pour kallisto
+
+```
+bedtools getfasta -name -fi ~/[PATH]/genomes/Homo_sapiens.GRCh37.dna.primary_assembly.fa -bed GenesAndRT_10000bases_tete.bed -fo Homo_sapiens.GRCh37.GenesAndRT.fasta
+```
+
+## Step 4 : index & quant kallisto (PSMN) v46.2
+
+```
+kallisto index -i GRCh37_GenesAndRT ../genome/Homo_sapiens.GRCh37.GenesAndRT.fasta
+
+kallisto quant -i kallisto_idx/GRCh37_GenesAndRT -t 32 -o kallisto/5Y_siDDX5-17_B1 fastq/5Y_siDDX5-17_B1_R1_cutadapt_match.fastq.gz fastq/5Y_siDDX5-17_B1_R2_cutadapt_match.fastq.gz
+
+kallisto quant -i kallisto_idx/GRCh37_GenesAndRT -t 32 -o kallisto/5Y_siDDX5-17_B2 fastq/5Y_siDDX5-17_B2_R1_cutadapt_match.fastq.gz fastq/5Y_siDDX5-17_B2_R2_cutadapt_match.fastq.gz
+
+kallisto quant -i kallisto_idx/GRCh37_GenesAndRT -t 32 -o kallisto/5Y_siDDX5-17_B3 fastq/5Y_siDDX5-17_B3_R1_cutadapt_match.fastq.gz fastq/5Y_siDDX5-17_B3_R2_cutadapt_match.fastq.gz
+
+
+kallisto quant -i kallisto_idx/GRCh37_GenesAndRT -t 32 -o kallisto/5Y_siGL2_B1 fastq/5Y_siGL2_B1_R1_cutadapt_match.fastq.gz fastq/5Y_siGL2_B1_R2_cutadapt_match.fastq.gz
+
+kallisto quant -i kallisto_idx/GRCh37_GenesAndRT -t 32 -o kallisto/5Y_siGL2_B2 fastq/5Y_siGL2_B2_R1_cutadapt_match.fastq.gz fastq/5Y_siGL2_B2_R2_cutadapt_match.fastq.gz
+
+kallisto quant -i kallisto_idx/GRCh37_GenesAndRT -t 32 -o kallisto/5Y_siGL2_B3 fastq/5Y_siGL2_B3_R1_cutadapt_match.fastq.gz fastq/5Y_siGL2_B3_R2_cutadapt_match.fastq.gz
+
+```
+
+## Step 5 : Formattage table de comptage et Detection des Readthrough par DESeq2
+
+```
+Rscript --vanilla ./src/DEG_RT.R --help
+Usage: ./src/DEG_RT.R [options]
+
+Options:
+ -d CHARACTER, --dir=CHARACTER
+ Directory with kallisto folders
+
+ -o CHARACTER, --out=CHARACTER
+ output repertory [default= ./]
+
+ -f NUMBER, --lfch=NUMBER
+ log2FoldChange Threshold [default= 4]
+
+ -t THREADS, --threads=THREADS
+ Number of process parallelization [default= 1]
+
+ -h, --help
+ Show this help message and exit
+
+
+Rscript --vanilla ./src/DEG_RT.R -d "./data/kallisto/siDDX/" -o "./results/siDDX/" -t 4 -f 4
+ - Formatting input files
+ - DEG analysis
+converting counts to integer mode
+estimating size factors
+estimating dispersions
+gene-wise dispersion estimates
+mean-dispersion relationship
+final dispersion estimates
+fitting model and testing
+
+
+|Log2FoldChange| Threshold > 4
+Number of genes with Readthrough : 3396
+ - Plots
+
+ Rscript --vanilla ./src/DEG_RT.R -d "./data/kallisto/siGL2/" -o "./results/siGL2/" -t 4 -f 4
+ - Formatting input files
+ - DEG analysis
+converting counts to integer mode
+estimating size factors
+estimating dispersions
+gene-wise dispersion estimates
+mean-dispersion relationship
+final dispersion estimates
+fitting model and testing
+
+
+|Log2FoldChange| Threshold > 4
+Number of genes with Readthrough : 3353
+ - Plots
+
+
+```
+
+## Step 5b : Differentiel entre les RT d'une condition (eg siDDX) vs Ctrl (eg siGL2)
+
+
+```
+Rscript --vanilla ./src/DEG_2cond.R --help
+Usage: ./src/DEG_2cond.R [options]
+
+
+Options:
+ -a CHARACTER, --cond1=CHARACTER
+ csv file with raw counts for the condition 1
+
+ -b CHARACTER, --cond2=CHARACTER
+ csv file with raw counts for the condition 2 (control condition)
+
+ -o CHARACTER, --out=CHARACTER
+ output repertory [default= ./]
+
+ -f NUMBER, --lfch=NUMBER
+ log2FoldChange Threshold [default= 0.4]
+
+ -h, --help
+ Show this help message and exit
+
+
+Rscript --vanilla ./src/DEG_2cond.R -a "./results/siDDX/rawcounts.csv" -b "./results/siGL2/rawcounts.csv" -o "./results/siDDX-vs-siGL2/" -f 0.4
+ - Formatting input files
+ - DEG analysis
+estimating size factors
+estimating dispersions
+gene-wise dispersion estimates
+mean-dispersion relationship
+final dispersion estimates
+fitting model and testing
+
+
+|Log2FoldChange| Threshold > 0.4
+Number of genes with Readthrough : 1345
+ - Plots
+ - Done
+
+
+
+```
+
+N.B : On retrouve significatifs les marqueurs vaidés dans [Terrone et al, 2022](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458439/), Figure 1B :
+- NCS1
+- PPARD
+- RAB36
+- NCKAP5L
+
+Le gène SH3TC1 n'a pas de RT significativement variable entre siDDX vs siGL2
+
+/!\ créer un argument pour ajouter un coldata (meme si valeur pa defaut)
+/!\ sortie finale avec colonnes moyenne d'expression du last exon sans RT ( basemean pour chaque condition, dc 2 colonnes )
+/!\ sortie finale avec colonnes moyenne d'expression ( basemean pour chaque condition, dc 2 colonnes ) du gene total sans RT (mais pas dans l'analyse stat)
+
+
+
+## Step 6 : Selection des genes diff sig & comptage des reads / bases
+
+1 - selection des genes DE sig,
+2 - BamCoverage sur les RT pour un vecteur de couverture sur les RT
+3 - Add Xavier Grand as dev
+
+
+
+
+## Step 7 : Bi-segmentation (fin du RT)
+
+
+## Step 8 : Ratio & formattage final
+
+
+
diff --git a/src/.docker_modules/readthroughbincounts/0.1/docker_init.sh b/src/.docker_modules/readthroughbincounts/0.1/docker_init.sh
new file mode 100755
index 0000000000000000000000000000000000000000..6d3e2df8e0a50b88ec5455694f2ae4a8a7e08e36
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/docker_init.sh
@@ -0,0 +1,5 @@
+#!/bin/sh
+# docker pull lbmc/readthroughbincounts:0.1
+docker build src/.docker_modules/readthroughbincounts/0.1 -t 'lbmc/readthroughbincounts:0.1'
+# docker push lbmc/readthroughbincounts:0.1
+# docker buildx build --platform linux/amd64,linux/arm64 -t "lbmc/readthroughbincounts:0.1" --push src/.docker_modules/readthroughbincounts/0.1
\ No newline at end of file
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/DEG_2cond.R b/src/.docker_modules/readthroughbincounts/0.1/src/DEG_2cond.R
new file mode 100644
index 0000000000000000000000000000000000000000..4ea8a1eaf2578086bf65f05edb14127c8753c9bd
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/DEG_2cond.R
@@ -0,0 +1,253 @@
+#!/usr/bin/env Rscript
+
+########################
+### 2023-08-21 #########
+### H. Polveche ########
+########################
+
+
+################
+### Params #####
+################
+
+set.seed(123) # Random reproducible
+
+library(optparse)
+
+option_list = list(
+ make_option(c("-a", "--cond1"), type="character", default=NULL,
+ help="csv file with raw counts for the condition 1", metavar="character"),
+ make_option(c("-b", "--cond2"), type="character", default=NULL,
+ help="csv file with raw counts for the condition 2 (control condition)", metavar="character"),
+ make_option(c("-o", "--out"), type="character", default="./",
+ help="output repertory [default= %default]", metavar="character"),
+ make_option(c("-f", "--lfch"), type="double", default=0.4,
+ help="log2FoldChange Threshold [default= %default]", metavar="number")
+);
+
+opt_parser = OptionParser(option_list=option_list);
+opt = parse_args(opt_parser);
+
+
+################
+### Packages ###
+################
+
+suppressPackageStartupMessages(library(tidyverse, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(DESeq2, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(viridis, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(gplots, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(openxlsx, quietly = T, warn.conflicts = F))
+
+#################
+### Functions ###
+#################
+
+custom.xlsx <- function(wb, tabl, n1, n2, n.sh, namesheet){
+ ## custom xlsx final file
+
+ addWorksheet(wb, namesheet)
+ writeData(wb, sheet = n.sh, tabl, rowNames = FALSE)
+
+ hs <- createStyle(fontSize = 10, fgFill = "#dee6ef",
+ halign = "center", valign = "center", textDecoration = "Bold",
+ border = "TopBottomLeftRight") #, textRotation = 45)
+
+ co.style <- createStyle(fontSize = 10,
+ halign = "center", valign = "center")
+
+ cond1.style <- createStyle(fontSize = 10, fgFill = "#ffffd7",
+ halign = "center", valign = "center")
+ cond2.style <- createStyle(fontSize = 10, fgFill = "#e8f2a1",
+ halign = "center", valign = "center")
+ sig.style <- createStyle(fontSize = 10, fgFill = "#729fcf",
+ halign = "center", valign = "center")
+
+ addStyle(wb, n.sh , co.style, rows = 2:nrow(tabl),
+ cols = 1:ncol(tabl), gridExpand = T)
+ addStyle(wb, n.sh , hs, rows = 1, cols = 1:ncol(tabl))
+ addStyle(wb, n.sh , hs, rows = 2:nrow(tabl), cols = 1)
+ addStyle(wb, n.sh , cond1.style, rows = 2:nrow(tabl),
+ cols = 8:(7+length(n1)), gridExpand = T)
+ addStyle(wb, n.sh , cond2.style, rows = 2:nrow(tabl), gridExpand = T,
+ cols = (8+length(n1)):(7+length(n1)+length(n2)) )
+ addStyle(wb, n.sh, sig.style, rows = 2:nrow(tabl), cols = 6:7, gridExpand = T)
+
+ setColWidths(wb, sheet = n.sh, cols = 1, widths = 30)
+ setColWidths(wb, sheet = n.sh, cols = 2:ncol(tabl), widths = 10)
+
+ return(wb)
+}
+
+
+DEG_conds <- function(cts.cond1 , cts.cond2 , output = "./", LFCh = 0.4 ){
+ ### cts.cond1 : rawcount file (csv) to condition (eg. siDDX)
+ ### cts.cond2 : rawcounts file (csv) to control consition (eg. siGL2)
+ ### output : directory for results
+ ### LFCh : Log2FoldChange threshold
+ ### DEG with DESeq2 to Find Readthrough
+
+ message(" - Formatting input files")
+
+ cts.cond1 <- read.csv2(cts.cond1, header = T) %>%
+ select(c(ID, ends_with("_RT")))
+
+ names.cond1 <- colnames(cts.cond1)[c(2:ncol(cts.cond1))]
+
+ cts.cond2 <- read.csv2(cts.cond2, header = T)%>%
+ select(c(ID, ends_with("_RT")))
+
+ names.cond2 <- colnames(cts.cond2)[c(2:ncol(cts.cond2))]
+
+ cts <- merge(cts.cond1, cts.cond2, by = "ID")
+ rownames(cts) <- cts$ID
+ cts <- cts[,c(2:ncol(cts))]
+
+ coldata <- as.data.frame(matrix(nc=2, nr = length(names.cond1) + length(names.cond2) ))
+ colnames(coldata) <- c("sampleNames", "condition")
+ coldata$sampleNames <- c(names.cond1, names.cond2)
+ coldata$condition <- as.factor(c(rep("cond1", length(names.cond1)) , rep("cond2", length(names.cond2)) ))
+
+
+ message(" - DEG analysis")
+ cts.1 <- data.frame(cts, moy=NA)
+ for (i in 1:nrow(cts.1)){
+ cts.1[i, "moy"] <- mean(as.numeric(cts.1[i , c(1:ncol(cts))]))
+ }
+ cts.2 <- cts.1[which(cts.1$moy > 5),]
+ cts.filtre <- cts.2[, c(1:ncol(cts))]
+ colnames(cts.filtre) <- colnames(cts)
+
+ cts.filtre <- cts.filtre[,c(order(colnames(cts.filtre)))]
+ coldata <- coldata[order(coldata$sampleName),]
+
+ dds <- DESeqDataSetFromMatrix(countData = cts.filtre, colData = coldata,
+ design = ~ condition )
+ dds <- DESeq(dds)
+
+
+ counts_normalise <- counts(dds, norm=T)
+ write.table(counts_normalise,
+ file=paste0(output, "normcounts.csv"),
+ sep=";", dec=",")
+
+ write.table(counts(dds, norm=F),
+ file=paste0(output, "rawcounts.csv"),
+ sep=";", dec=",")
+
+ resGA <- results(dds, contrast=c("condition","cond1", "cond2"),
+ lfcThreshold=LFCh, altHypothesis="greaterAbs") # lfcThreshold=0.4
+ message(" \n")
+ message (paste0("|Log2FoldChange| Threshold > ", LFCh))
+ message(paste0( "Number of genes with Readthrough : ",
+ nrow(resGA[which((resGA$padj < 0.05) & resGA$baseMean > 20 ),]) # Up
+ ))
+
+
+ message(" - Plots")
+ rld <- rlogTransformation(dds, blind=TRUE, fitType = "local")
+ vsd <- varianceStabilizingTransformation(dds, blind=TRUE, fitType = "local")
+ vstMat = assay(vsd)
+
+ pdf(paste0(output, "/DEG_plots.pdf"))
+
+ condcols=c("firebrick","steelblue")
+ names(condcols)=unique(coldata$condition)
+
+ ylim <- c(-10,10)
+ drawLines <- function() abline(h=c(-0.4,0.4),col="steelblue",lwd=2)
+ plotMA(resGA, ylim=ylim); drawLines()
+
+ hits=rownames(resGA[which((resGA$padj < 0.05) & resGA$baseMean > 20 ),])
+
+ plot(resGA$log2FoldChange,-log(resGA$padj,10),
+ ylab='-log10(Adjusted P)',
+ xlab="Log2 FoldChange",
+ pch=19,cex=0.5, col = "dimgray"
+ )
+
+ points(resGA[hits,'log2FoldChange'],
+ -log(resGA[hits,'padj'],10),
+ pch=19,
+ cex=0.5,
+ col="steelblue"
+ )
+ abline(h=-log10(0.05),lty=3)
+ abline(v=-LFCh,lty=3)
+ abline(v=LFCh,lty=3)
+
+
+ barplot(colSums(counts(dds, normalized=F)), col=condcols[as.factor(coldata$condition)],
+ las=2,cex.names=0.4,
+ main='Pre Normalised Counts')
+
+ barplot(colSums(counts(dds, normalized=T)), col=condcols[as.factor(coldata$condition)],
+ las=2,cex.names=0.4,
+ main='Post Normalised Counts')
+
+ pcaData <- plotPCA(rld, intgroup=c("condition"), returnData=TRUE)
+ percentVar <- round(100 * attr(pcaData, "percentVar"))
+
+ ggplot(pcaData, aes(PC1, PC2, color=condition)) +
+ geom_point(size=3) +
+ xlab(paste0("PC1: ",percentVar[1],"% variance")) +
+ ylab(paste0("PC2: ",percentVar[2],"% variance")) +
+ coord_fixed()
+
+ sampleDists <- dist( t( assay(rld) ) )
+ sampleDistMatrix <- as.matrix( sampleDists )
+ colours <- inferno(255)
+ heatmap.2( sampleDistMatrix, trace="none", col=colours, margins=c(15,15),
+ cexRow=0.5, cexCol=0.5)
+
+ plotDispEsts(dds)
+
+ dev.off()
+
+ write.table(resGA, paste0(output, "cond1-vs-cond2_all_genes.csv"),
+ sep = ";", dec = ",")
+ write.table(resGA[which((resGA$padj < 0.05) & resGA$baseMean > 20 ),],
+ paste0(output, "cond1-vs-cond2_sig_log2FC", LFCh,"_padj005_BM20.csv"),
+ sep = ";", dec = ",")
+
+
+ message(" - Final Excel File")
+
+ resGA.m <- merge(as.data.frame(resGA), round(counts_normalise, digit = 2), by = "row.names")
+ colnames(resGA.m)[1] <- "ID"
+ resGA.m[,c(2:5)] <- round(resGA.m[,c(2:5)], digits = 2)
+ res.sig.m <- resGA.m[which((resGA$padj < 0.05) & resGA$baseMean > 20 ),]
+
+ wb <- createWorkbook()
+ wb <- custom.xlsx(wb=wb, tabl = res.sig.m, n1 = names.cond1,
+ n2 = names.cond2, n.sh = 1, namesheet = "sig")
+ wb <- custom.xlsx(wb, resGA.m, names.cond1, names.cond2, 2, "all")
+ saveWorkbook(wb, paste0(output,"cond1-vs-cond2_DESeq2_results.xlsx"), overwrite = TRUE)
+
+ message(" - Done")
+}
+
+
+
+#################
+### __main__ ####
+#################
+
+
+# cts.cond1 <- "./results/siDDX/rawcounts.csv"
+# cts.cond2 <- "./results/siGL2/rawcounts.csv"
+# output <- "./results/siDDX-vs-siGL2/"
+# LFCh <- 0.4
+
+
+DEG_conds(cts.cond1 = opt$cond1, cts.cond2 = opt$cond2, output = opt$out, LFCh = opt$lfch)
+# DEG_conds(cts.cond1 , cts.cond2 , output, LFCh)
+
+
+
+
+
+
+
+
+
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/DEG_RT.R b/src/.docker_modules/readthroughbincounts/0.1/src/DEG_RT.R
new file mode 100644
index 0000000000000000000000000000000000000000..7cd5545a0e3799e5d9cb80dce87dc159a1d9e6eb
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/DEG_RT.R
@@ -0,0 +1,251 @@
+#!/usr/bin/env Rscript
+
+########################
+### 2023-08-03 #########
+### H. Polveche ########
+########################
+
+
+################
+### Params #####
+################
+
+set.seed(123) # Random reproducible
+
+
+
+library(optparse)
+
+
+option_list = list(
+ make_option(c("-d", "--dir"), type="character", default=NULL,
+ help="Directory with kallisto folders", metavar="character"),
+ make_option(c("-o", "--out"), type="character", default="./",
+ help="output repertory [default= %default]", metavar="character"),
+ make_option(c("-f", "--lfch"), type="double", default=4,
+ help="log2FoldChange Threshold [default= %default]", metavar="number"),
+ make_option(c("-t", "--threads"), type="integer", default=1,
+ help="Number of process parallelization [default= %default]")
+ );
+
+opt_parser = OptionParser(option_list=option_list);
+opt = parse_args(opt_parser);
+
+
+if (is.null(opt$dir)){
+ print_help(opt_parser)
+ stop("At least one argument must be supplied (input directory).n", call.=FALSE)
+}
+
+n.worked <- opt$threads
+
+
+
+################
+### Packages ###
+################
+
+suppressPackageStartupMessages(library(tidyverse, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(doFuture, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(DESeq2, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(viridis, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(gplots, quietly = T, warn.conflicts = F))
+
+
+
+#################
+### Functions ###
+#################
+
+registerDoFuture()
+plan(cluster, workers = n.worked)
+
+format_table_RT_1file <- function(file = "./abundance.tsv", name = "toto" ){
+ ### file abundance kallisto output
+ ### passer de 1 colonne a 2 colonne gene et gene_RT
+
+ kal <- read.csv2(file, header = T, sep = "\t", dec = ".") %>%
+ select(target_id, est_counts) %>%
+ mutate( RTdetect = str_detect(string = target_id, pattern = "_RT$"))
+
+ kal.genes <- kal %>%
+ filter( RTdetect == FALSE) %>%
+ select(target_id, est_counts)
+ colnames(kal.genes)[2] <- name
+
+ kal.RT <- kal %>%
+ filter( RTdetect == TRUE) %>%
+ select(target_id, est_counts) %>%
+ mutate(target_id = str_replace(target_id, "_RT", "") )
+ colnames(kal.RT)[2] <- paste0(name,"_RT")
+
+ res <- merge(kal.genes, kal.RT, by = "target_id")
+
+ return(res)
+}
+
+
+
+format_tables_toDESeq2 <- function(dir = "./"){
+ ### dir : directory with kallisto folders
+
+ if ( !(dir.exists(dir)) ){
+ stop(paste0("The directory '", dir,"' does not exist."))
+ }
+
+ list_dir <- list.files(path = dir, full.names = F)
+
+ dfs <- foreach(i = 1:length(list_dir), .combine=cbind) %dopar% #, .combine=cbind)
+ format_table_RT_1file(file = paste0(dir, list_dir[i], "/abundance.tsv"), name = list_dir[i] )
+
+ colnames(dfs)[1] <- "ID"
+ dfs <- dfs %>%
+ select(!target_id)
+
+ dfs[ ,c(2:ncol(dfs))] <- round( dfs[ ,c(2:ncol(dfs))] )
+
+ #reg.ex <- commun_expression(list_dir)
+ coldata <- data.frame( sampleName = colnames(dfs)[c(2:ncol(dfs))], condition = rep(c("canonical", "RT"), (ncol(dfs) - 1)/2))
+ rownames(coldata) <- coldata$sampleName
+
+ return(list("counts" = dfs, "coldata" = coldata))
+}
+
+
+
+DEG_RT <- function(input = "./data/kallisto/", output = "./results/", LFCh = 4 ){
+ ### input : directory with kallisto folders
+ ### output : directory for results
+ ### LFCh : Log2FoldChange threshold
+ ### DEG with DESeq2 to Find Readthrough
+
+ message(" - Formatting input files")
+ mat <- format_tables_toDESeq2(dir = input)
+
+ cts <- mat$counts
+ write_excel_csv(cts, paste0(output, "rawcounts.csv"), col_names = T, delim = ";")
+
+ rownames(cts) <- cts$ID
+ cts <- cts[,c(2:ncol(cts))]
+
+ coldata <- mat$coldata
+ write_excel_csv(coldata, paste0(output, "coldata.csv"), col_names = T, delim = ";")
+ coldata$condition <- as.factor(coldata$condition)
+
+ message(" - DEG analysis")
+ cts.1 <- data.frame(cts, moy=NA)
+ for (i in 1:nrow(cts.1)){
+ cts.1[i, "moy"] <- mean(as.numeric(cts.1[i , c(1:ncol(cts))]))
+ }
+ cts.2 <- cts.1[which(cts.1$moy > 5),]
+ cts.filtre <- cts.2[, c(1:ncol(cts))] # 12949
+ colnames(cts.filtre) <- colnames(cts)
+
+ colnames(cts.filtre) <- c(paste0("X", colnames(cts.filtre)))
+ rownames(coldata) <- c(paste0("X", rownames(coldata)))
+
+ cts.filtre <- cts.filtre[,c(order(colnames(cts.filtre)))]
+ coldata <- coldata[order(coldata$sampleName),]
+
+ dds <- DESeqDataSetFromMatrix(countData = cts.filtre, colData = coldata,
+ design = ~ condition )
+ dds <- DESeq(dds)
+
+
+ counts_normalise <- counts(dds, norm=T)
+ write.table(counts_normalise,
+ file=paste0(output, "normcounts.csv"),
+ sep=";", dec=",")
+
+
+
+ resGA <- results(dds, contrast=c("condition","RT", "canonical"),
+ lfcThreshold=LFCh, altHypothesis="greater") # lfcThreshold=0.4
+ message(" \n")
+ message (paste0("|Log2FoldChange| Threshold > 4"))
+ message(paste0( "Number of genes with Readthrough : ",
+ nrow(resGA[which((resGA$padj < 0.05) & resGA$baseMean > 20 ),]) # Up
+ ))
+
+
+ message(" - Plots")
+ rld <- rlogTransformation(dds, blind=TRUE, fitType = "local")
+ vsd <- varianceStabilizingTransformation(dds, blind=TRUE, fitType = "local")
+ vstMat = assay(vsd)
+
+ pdf(paste0(output, "/DEG_plots.pdf"))
+
+ condcols=c("firebrick","steelblue")
+ names(condcols)=unique(coldata$condition)
+
+ ylim <- c(-10,10)
+ drawLines <- function() abline(h=c(-0.4,0.4),col="steelblue",lwd=2)
+ plotMA(resGA, ylim=ylim); drawLines()
+
+ hits=rownames(resGA[which((resGA$padj < 0.05) & resGA$baseMean > 20 ),])
+
+ plot(resGA$log2FoldChange,-log(resGA$padj,10),
+ ylab='-log10(Adjusted P)',
+ xlab="Log2 FoldChange",
+ pch=19,cex=0.5, col = "dimgray"
+ )
+
+ points(resGA[hits,'log2FoldChange'],
+ -log(resGA[hits,'padj'],10),
+ pch=19,
+ cex=0.5,
+ col="steelblue"
+ )
+ abline(h=-log10(0.05),lty=3)
+ abline(v=-LFCh,lty=3)
+ abline(v=LFCh,lty=3)
+
+
+ barplot(colSums(counts(dds, normalized=F)), col=condcols[as.factor(coldata$condition)],
+ las=2,cex.names=0.4,
+ main='Pre Normalised Counts')
+
+ barplot(colSums(counts(dds, normalized=T)), col=condcols[as.factor(coldata$condition)],
+ las=2,cex.names=0.4,
+ main='Post Normalised Counts')
+
+ pcaData <- plotPCA(rld, intgroup=c("condition"), returnData=TRUE)
+ percentVar <- round(100 * attr(pcaData, "percentVar"))
+
+ ggplot(pcaData, aes(PC1, PC2, color=condition)) +
+ geom_point(size=3) +
+ xlab(paste0("PC1: ",percentVar[1],"% variance")) +
+ ylab(paste0("PC2: ",percentVar[2],"% variance")) +
+ coord_fixed()
+
+ sampleDists <- dist( t( assay(rld) ) )
+ sampleDistMatrix <- as.matrix( sampleDists )
+ colours <- inferno(255)
+ heatmap.2( sampleDistMatrix, trace="none", col=colours, margins=c(15,15),
+ cexRow=0.5, cexCol=0.5)
+
+ plotDispEsts(dds)
+
+ dev.off()
+
+ write.table(resGA, paste0(output, "RT-vs-Canonical_all_genes.csv"),
+ sep = ";", dec = ",")
+ write.table(resGA[which((resGA$padj < 0.05) & resGA$baseMean > 20 ),],
+ paste0(output, "RT-vs-Canonical_sig_log2FC", LFCh,"_padj005_BM20.csv"),
+ sep = ";", dec = ",")
+
+ message(" - Done")
+}
+
+
+
+#################
+### __main__ ####
+#################
+
+DEG_RT(input = opt$dir, output = opt$out, LFCh = opt$lfch)
+#DEG_RT(input = "./data/kallisto/siGL2/", output = "./results/", LFCh = 4)
+
+
+
+
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/RangeCoverage.R b/src/.docker_modules/readthroughbincounts/0.1/src/RangeCoverage.R
new file mode 100644
index 0000000000000000000000000000000000000000..090da7c53f8d01280bf6cbb6c19115b6c8fce136
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/RangeCoverage.R
@@ -0,0 +1,77 @@
+#!/usr/bin/env Rscript
+
+########################
+### 2023-08-04 #########
+### H. Polveche ########
+########################
+
+
+################
+### Params #####
+################
+
+set.seed(123) # Random reproducible
+
+
+# library(optparse)
+#
+#
+# option_list = list(
+# make_option(c("-d", "--dir"), type="character", default=NULL,
+# help="Directory with kallisto folders", metavar="character"),
+# make_option(c("-o", "--out"), type="character", default="./",
+# help="output repertory [default= %default]", metavar="character"),
+
+# );
+#
+# opt_parser = OptionParser(option_list=option_list);
+# opt = parse_args(opt_parser);
+#
+#
+# if (is.null(opt$dir)){
+# print_help(opt_parser)
+# stop("At least one argument must be supplied (input directory).n", call.=FALSE)
+# }
+
+
+################
+### Packages ###
+################
+
+suppressPackageStartupMessages(library(tidyverse, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(rtracklayer, quietly = T, warn.conflicts = F))
+#suppressPackageStartupMessages(library(doFuture, quietly = T, warn.conflicts = F))
+
+library(bamsignals)
+
+
+rangeBed <- function(resGA = "./results/siDDX5-17/RT-vs-Canonical_sig_log2FC4_padj005_BM20.csv",
+ bed = "./results/RT-Only_10000bases_essai.bed"){
+ ### ne garder que les coordonnees de RT qui sont DEG sig
+
+
+
+
+}
+
+countBAMwtBED <- function(bedfile, bamPath){
+ ### bedfile : result de bintab()
+ ### "./results/Regions_50bins_tutu.bed"
+ ### bamPath : chemin du fichier bam
+ ### "./results/DDX_6_aligned_sorted.filter.bin50.bam"
+
+ gr_obj <- rtracklayer::import(bedfile)
+ bamFile <- Rsamtools::BamFile(bamPath)
+
+ sigs.c <- bamCount(bamPath, gr_obj, mapq = 10, verbose=FALSE)
+ sigs.p <- bamCoverage(bamPath, gr_obj, mapq = 10, verbose=FALSE)
+
+ df.bin.c <- data.frame(df.bin, count=NA, moy=NA)
+ df.bin.c[, "count"] <- sigs.c
+ df.bin.c[, "moy"] <- round(sigs.c / 50 )
+
+
+ return(list("counts" = df.bin.c, "coverage" = sigs.p))
+}
+
+
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/Rthrough.R b/src/.docker_modules/readthroughbincounts/0.1/src/Rthrough.R
new file mode 100644
index 0000000000000000000000000000000000000000..0b68daeec6b8dde51c11f9cc8af4d482dacfab5e
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/Rthrough.R
@@ -0,0 +1,124 @@
+#!/usr/bin/env Rscript
+
+########################
+### 2023-07-27 #########
+### H. Polveche ########
+########################
+
+### script --vanilla ./src/readthrough_bin.R
+
+
+#library("optparse")
+
+# option_list = list(
+# make_option(c("-f", "--file"), type="character", default=NULL,
+# help="dataset file name", metavar="character"),
+# make_option(c("-o", "--out"), type="character", default="out.txt",
+# help="output file name [default= %default]", metavar="character")
+# );
+#
+# opt_parser = OptionParser(option_list=option_list);
+# opt = parse_args(opt_parser);
+#
+
+# if (is.null(opt$file)){
+# print_help(opt_parser)
+# stop("At least one argument must be supplied (input file).n", call.=FALSE)
+# }
+
+# ## program...
+# df = read.table(opt$file, header=TRUE)
+# num_vars = which(sapply(df, class)=="numeric")
+# df_out = df[ ,num_vars]
+# write.table(df_out, file=opt$out, row.names=FALSE)
+
+#Rscript --vanilla yasrs.R -f iris.txt -o out.txt
+
+
+#################
+### Variables ###
+#################
+
+fileIN <- "./data/readthrough_range.bed"
+#pathOUT <- "./results/"
+#n.worked <- 6
+#suffix <- "toto"
+
+
+
+################
+### Packages ###
+################
+
+library(tidyverse)
+library(progress) # progress bar
+library(doFuture) # parallelism
+library(GenomicRanges)
+library(valr)
+library(Rsamtools)
+library(bamsignals)
+library(rtracklayer)
+
+
+##############
+### Config ###
+##############
+
+
+set.seed(123) # Random reproducible
+
+## registerDoFuture()
+## plan(cluster, workers = n.worked)
+#plan(multisession, workers = n.worked)
+
+source(file = "./src/readthrough_bin.R")
+
+# message("Number of parallel workers: ", nbrOfWorkers())
+
+bed <- read.csv2(fileIN, sep ="\t", header = F)
+### LAAAA
+vars <- normalize.stranded(bedVar = bed, suf = "tutu", pathOUT = "./results/")
+df.bin <- bintab(vars = vars, bin = 50, n.worked = 6, suf = "tutu", pathOUT = "./results/")
+
+cp <- countBAMwtBED(bedfile = "./results/Regions_50bins_tutu.bed",
+ bamPath = "./data/BAM/5Y_siDDX5-17_B1/5Y_siDDX5-17_B1.bam")
+counts <- cp$counts
+coverage <- cp$profile
+counts.3 <- counts[which(counts$moy >= 3),]
+
+
+
+
+
+
+
+####################
+### Progress Bar ###
+####################
+
+n_iter <- 200
+pb <- progress_bar$new(format = "(:spin) [:bar] :percent [Elapsed time: :elapsedfull || Estimated time remaining: :eta]",
+ total = n_iter,
+ complete = "=", # Completion bar character
+ incomplete = "-", # Incomplete bar character
+ current = ">", # Current bar character
+ clear = FALSE, # If TRUE, clears the bar when finish
+ width = 200) # Width of the progress bar
+
+for(i in 1:n_iter) {
+
+ # Updates the current state
+ pb$tick()
+
+ #---------------------
+ # Code to be executed
+ #---------------------
+
+ Sys.sleep(0.1) # Remove this line and add your code
+
+ #---------------------
+
+}
+
+
+
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/install_packages.R b/src/.docker_modules/readthroughbincounts/0.1/src/install_packages.R
new file mode 100644
index 0000000000000000000000000000000000000000..dd4c6aff9ae57b4a410d920a07a6da368b7aa69e
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/install_packages.R
@@ -0,0 +1,22 @@
+#!/bin/Rscript
+
+### Author: Xavier Grand
+### Date: 23/10/2023
+
+# Packages installation:
+
+list.of.packages <- c("BiocManager", "progress", "doFuture", "viridis",
+ "gplots", "openxlsx", "optparse")
+
+new.packages <- list.of.packages[!(list.of.packages %in%
+ installed.packages()[, "Package"])]
+if(length(new.packages)) install.packages(new.packages, dependencies = T)
+
+list.of.BiocPackages <- c("rtracklayer", "GenomicRanges", "DESeq2", "Rsamtools", "bamsignals")
+new.BiocPackages <- list.of.BiocPackages[!(list.of.BiocPackages %in% installed.packages()[,"Package"])]
+
+if (length(new.BiocPackages) > 0) {
+ BiocManager::install(new.BiocPackages, dependencies = TRUE, ask = FALSE)
+}
+
+install.packages("valr", dependencies = T)
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/readthrough_bin.R b/src/.docker_modules/readthroughbincounts/0.1/src/readthrough_bin.R
new file mode 100644
index 0000000000000000000000000000000000000000..9fe2d1bc0470cd1467cd68c884ea4dc89ab2722d
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/readthrough_bin.R
@@ -0,0 +1,169 @@
+########################
+### 2023-07-24 #########
+### H. Polveche ########
+########################
+
+
+#################
+### Functions ###
+#################
+
+
+
+normalize.stranded <- function(bedVar, suf = "suf", pathOUT = "./"){
+ ### bedVar : tableau de sortie du programme python ReadThrough X. Grand
+ ### https://gitbio.ens-lyon.fr/xgrand/readthrough/-/tree/master/
+ ### suf : suffix to output bed
+ ### pathOUT : chemin pour les resultats
+ ### Formatage du tableau de sortie du programme de X. Grand
+
+
+ vec.chr <- c(1:23, "X", "Y", "MT")
+
+ dt <- data.frame(bedVar, start.exon=NA, end.exon=NA, region500=NA,
+ end.rt = NA, V14=NA, V15=NA)
+ dt <- dt %>%
+ mutate(start.exon = case_when(V6 == "+" ~ V9,
+ V6 == "-" ~ V10
+ )) %>%
+ mutate(end.exon = case_when(V6 == "+" ~ V10,
+ V6 == "-" ~ V9
+ )) %>%
+ mutate(region500 = case_when(V6 == "+" ~ V2,
+ V6 == "-" ~ V3
+ )) %>%
+ mutate(end.rt = case_when(V6 == "+" ~ V3,
+ V6 == "-" ~ V2
+ )) %>%
+ mutate(V14 = case_when(V6 == "+" ~ V2,
+ V6 == "-" ~ V3
+ )) %>%
+ mutate(V15 = case_when(V6 == "+" ~ V3,
+ V6 == "-" ~ V2
+ )) %>%
+ select(V1, V4, V6, V7, start.exon, end.exon, region500, end.rt, V14, V15) %>%
+ dplyr::rename("chr" = "V1",
+ "strand" = "V6",
+ "gene_symbol" = "V7",
+ "ENSG" = "V4") %>%
+ filter(chr %in% vec.chr)
+
+ bedT <- dt[,c("chr", "V14", "V15", "gene_symbol")]
+ colnames(bedT) <- c("chr","start","end", "gene_symbol")
+ dt <- dt %>%
+ select(chr, strand, gene_symbol, ENSG, start.exon, end.exon, region500, end.rt)
+ write_tsv(bedT, paste0(pathOUT,"Regions10500bases_toBedtools_", suf, ".bed"),
+ col_names = F )
+ write_excel_csv(dt, paste0(pathOUT,"Regions10500bases_Coordinates_infos_", suf, ".csv"),
+ delim = ";" )
+
+ return(list("table" = dt, "bed" = bedT))
+}
+
+
+
+OneGeneBin <- function(bedT, tab, bin = 50){
+ ### bedT : sortie 'bed' de la fonction normalize.stranded(),
+ ### ligne i de la fonction bintab()
+ ### tab : sortie 'table' de la fonction normalize.stranded(),
+ ### ligne i de la fonction bintab()
+ ### bon : taille d'un bin pour le decoupage
+ ### Pour un ligne ( = chaque gene ) on va couper la région 500+10k bases
+ ### en bin de {bin}
+
+ if ( ((abs(bedT[1, "start"] - bedT[1, "end"])) %% bin) %in% 0){
+ stra <- tab[1, "strand"]
+ end.ex <- tab[1, "end.exon"]
+ repet <- abs(bedT[1, "start"] - bedT[1, "end"]) / bin + 1
+ tabi <- as.data.frame(matrix(nc=11, nr = repet -1))
+ colnames(tabi) <- c("chr", "start", "end", "ID", "bins", "strand",
+ "gene_symbol", "ENSG", "category","s.bed", "e.bed")
+ tabi[, "gene_symbol"] <- rep(tab[1, "gene_symbol"], repet -1)
+ tabi[, "chr"] <- rep(tab[1, "chr"], repet -1)
+ tabi[, "ENSG"] <- rep(tab[1, "ENSG"], repet -1)
+ tabi[, "strand"] <- rep(stra, repet -1)
+
+
+ if(stra == "+"){
+ bin2 <- bin
+
+ vec <- seq(bedT[1, "start"], bedT[1, "end"], by = bin2)
+ tabi[, "start"] <- vec[1:(repet-1)]
+ tabi[, "s.bed"] <- vec[1:(repet-1)]
+ tabi[, "end"] <- vec[2:repet] - 1
+ tabi[, "e.bed"] <- vec[2:repet] - 1
+ tabi[, "bins"] <- seq(1:(repet-1))
+
+ } else {
+ bin2 <- (-1) * bin
+ vec <- seq(bedT[1, "start"], bedT[1, "end"], by = bin2)
+ tabi[, "start"] <- vec[1:(repet-1)]
+ tabi[, "end"] <- vec[2:repet] - 1
+ tabi[, "e.bed"] <- vec[1:(repet-1)]
+ tabi[, "s.bed"] <- vec[2:repet] - 1
+ tabi[, "bins"] <- seq(1:(repet-1))
+
+ }
+
+
+ tabi <- tabi %>%
+ mutate(ID = paste0(gene_symbol, "_", bins)) %>%
+ mutate(category = case_when(stra == "+" ~ ifelse(end.ex >= start, "EXON", "RT"),
+ stra == "-" ~ ifelse(end.ex >= start, "RT", "EXON")))
+
+ }
+}
+
+
+
+
+bintab <- function(vars, bin = 50, n.worked = 6, suf = "suf", pathOUT = "./"){
+ ### binage de tous les genes , parralelisation et optimisation de temps de calcul
+ ### vars : result fonction normalize.stranded()
+ ### suf : suffix to output bed
+ ### pathOUT : chemin pour les resultats
+
+ tab <- vars$table
+ bedT <- vars$bed
+
+ set.seed(123) # Random reproducible
+
+ registerDoFuture()
+ plan(cluster, workers = n.worked)
+
+ tabo <- foreach(i = 1:nrow(tab)) %dopar% {
+ OneGeneBin(bedT[i, ], tab[i, ], bin = 50)
+ }
+
+ tabo <- compact(tabo)
+ df <- dplyr::bind_rows(tabo)
+
+ write_tsv(df[,c("chr", "s.bed", "e.bed", "ID")], paste0(pathOUT,"Regions_", bin, "bins_",
+ suf, ".bed"), col_names = F )
+ write_excel_csv(df, paste0(pathOUT,"Regions_", bin, "bins_", suf, ".csv"), delim = ";" )
+
+ return(df)
+
+}
+
+
+countBAMwtBED <- function(bedfile, bamPath){
+ ### bedfile : result de bintab()
+ ### "./results/Regions_50bins_tutu.bed"
+ ### bamPath : chemin du fichier bam
+ ### "./results/DDX_6_aligned_sorted.filter.bin50.bam"
+
+ gr_obj <- rtracklayer::import(bedfile)
+ bamFile <- Rsamtools::BamFile(bamPath)
+
+ sigs.c <- bamCount(bamPath, gr_obj, mapq = 10, verbose=FALSE)
+ sigs.p <- bamCoverage(bamPath, gr_obj, mapq = 10, verbose=FALSE)
+
+ df.bin.c <- data.frame(df.bin, count=NA, moy=NA)
+ df.bin.c[, "count"] <- sigs.c
+ df.bin.c[, "moy"] <- round(sigs.c / 50 )
+
+
+ return(list("counts" = df.bin.c, "coverage" = sigs.p))
+}
+
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/refToKallisto.R b/src/.docker_modules/readthroughbincounts/0.1/src/refToKallisto.R
new file mode 100644
index 0000000000000000000000000000000000000000..3033218cd6bbea0159c250a5d7ad5da332aaec8c
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/refToKallisto.R
@@ -0,0 +1,170 @@
+#!/usr/bin/env Rscript
+
+########################
+### 2023-08-03 #########
+### H. Polveche ########
+########################
+
+
+################
+### Params #####
+################
+
+library(optparse)
+
+option_list = list(
+ make_option(c("-f", "--file"), type="character", default=NULL,
+ help="GTF File", metavar="character"),
+ make_option(c("-o", "--out"), type="character", default="./",
+ help="output repertory [default= %default]", metavar="character"),
+ make_option(c("-s", "--suffix"), type="character", default="readtrhough",
+ help="A suffix to specify your results [default= %default]", metavar="character"),
+ make_option(c("-r", "--RT"), type="integer", default=10000,
+ help="Size of Readthrough search zone after last gene exon (#bases) [default= %default]", metavar="number"),
+ make_option(c("-c", "--chr"), type="character", default="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,X,Y,MT",
+ help="List of chromosomes you want to keep (default: humain chr) [default= %default]")
+);
+
+opt_parser = OptionParser(option_list=option_list);
+opt = parse_args(opt_parser);
+
+
+if (is.null(opt$file)){
+ print_help(opt_parser)
+ stop("At least one argument must be supplied (input GTF file).n", call.=FALSE)
+}
+
+
+################
+### Packages ###
+################
+
+suppressPackageStartupMessages(library(tidyverse, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(GenomicRanges, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(valr, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(rtracklayer, quietly = T, warn.conflicts = F))
+suppressPackageStartupMessages(library(progress, quietly = T, warn.conflicts = F) )
+
+#################
+### Functions ###
+#################
+
+gtfConvert <- function(file, out , suf, RT, chr){
+ ### file gtf with grep function
+ ### e.g :
+ ### grep -P "\tgene\t" Homo_sapiens.GRCh37.75.gtf > Homo_sapiens.GRCh37.75.genes.gtf
+
+ vec.chr <- str_split(chr, ",")
+ vec.chr <- vec.chr[[1]]
+
+ message("Loading GTF file ( 1 / 6 )")
+ gtf <- rtracklayer::import(file)
+ gtf <- gtf[which(gtf$gene_biotype %in% "protein_coding"),]
+ gtf$score <- 0
+ gtf$name <- paste0(gtf$gene_name,"_", gtf$gene_id)
+
+
+ gtf10kb <- flank(gtf, start = FALSE, width = RT)
+ gtf10kb$name <- paste0(gtf10kb$name, "_RT")
+
+ message("Export classical Bed file ( 2 / 6 )")
+
+ rtracklayer::export(gtf, paste0(out, "Genes_", RT ,"bases_", suf ,".bed"), format="bed") #,object = gtf, genome = "hg19", format = "bed15", name = "GRCh37.75_genes")
+ rtracklayer::export(gtf10kb, paste0(out, "GenesAndRT_", RT ,"bases_", suf ,".bed"), format="bed")
+
+ gtf.r <- read_bed(paste0(out, "Genes_", RT ,"bases_", suf ,".bed")) %>%
+ filter(chrom %in% vec.chr)
+
+ # On ne conserve que les chr canoniques et on place à 0 si strand (-) au lieu de valeur neg
+ gtf10kb.r <- read_bed(paste0(out, "GenesAndRT_", RT ,"bases_", suf ,".bed")) %>%
+ filter(chrom %in% vec.chr) %>%
+ mutate(start = if_else(start < 0 , 0, start))
+ file.remove(paste0(out, "GenesAndRT_", RT ,"bases_", suf ,".bed"))
+
+ gtf10kb.r.val <- as.data.frame(gtf10kb.r) %>%
+ rename(X4 = "symbol" ,
+ X6 = "strand")
+ gtf.r.val <- as.data.frame(gtf.r) %>%
+ rename(X4 = "symbol" ,
+ X6 = "strand")
+
+ message(paste0("Create ", RT,"kb extension ( 3 / 6 )"))
+
+ # intersection pour avoir les zones RT chevauchant avec des genes
+ overl <- valr::bed_intersect(gtf10kb.r.val, gtf.r.val, suffix = c("_10kb", "")) %>%
+ filter(.overlap > 0) %>%
+ filter((strand_10kb == strand)) %>%
+ mutate(end_10kb = if_else(strand_10kb == "+", start, end_10kb)) %>%
+ mutate(start_10kb = if_else(strand_10kb == "-", end, start_10kb)) %>%
+ select(chrom, start_10kb, end_10kb, symbol_10kb, X5_10kb, strand_10kb) %>%
+ filter(start_10kb - end_10kb < 0)
+
+ message("Overlap on genes : coordinate correction ( 4 / 6 )")
+
+ # on corrige pour que la fin du RT ne soit pas de 10kb mais avant le debut du gene n+1
+ gtf10kb.r.val2 <- gtf10kb.r.val
+ pb <- progress_bar$new(format = " [:bar] :percent [Elapsed time: :elapsedfull || Estimated time remaining: :eta]", #(:spin)
+ total = nrow(overl),
+ complete = "=", # Completion bar character
+ incomplete = "-", # Incomplete bar character
+ current = ">", # Current bar character
+ clear = FALSE, # If TRUE, clears the bar when finish
+ width = 100) # Width of the progress bar
+
+ for (i in 1:nrow(overl)){
+ pb$tick()
+ if (overl[i, "symbol_10kb"] %in% gtf10kb.r.val2[,"symbol"]){
+ gtf10kb.r.val2[which(gtf10kb.r.val2$symbol %in%
+ overl[i, "symbol_10kb"]), c("start", "end")] <- overl[i, c("start_10kb", "end_10kb")]
+ }
+ }
+
+ message("Overlap on genes : Stranded correction ( 5 / 6 )")
+ pb <- progress_bar$new(format = " [:bar] :percent [Elapsed time: :elapsedfull || Estimated time remaining: :eta]", # (:spin)
+ total = nrow(gtf10kb.r.val2),
+ complete = "=", # Completion bar character
+ incomplete = "-", # Incomplete bar character
+ current = ">", # Current bar character
+ clear = FALSE, # If TRUE, clears the bar when finish
+ width = 100) # Width of the progress bar
+
+ # On garde les coordonnees des RT uniquement
+ write_excel_csv(gtf10kb.r.val2, paste0(out, "RT-Only_", RT ,"bases_", suf ,".bed"),
+ delim = "\t", col_names = F, quote="none")
+
+ # On met le debut du RT au meme niveau que le gene associe
+ for (i in 1:nrow(gtf10kb.r.val2)){
+ pb$tick()
+ if(gtf10kb.r.val2[i, "strand"] == "+"){
+ gtf10kb.r.val2[i, "start"] <- gtf.r.val[which(gtf.r.val$symbol %in% str_replace(gtf10kb.r.val2[i, "symbol"], "_RT", "")), "start"] #which(gtf.r.val$symbol %in% str_replace(gtf10kb.r.val2[i, "symbol"], "_RT", ""))
+
+ } else {
+ gtf10kb.r.val2[i, "end"] <- gtf.r.val[which(gtf.r.val$symbol %in% str_replace(gtf10kb.r.val2[i, "symbol"], "_RT", "")), "end"] #which(gtf.r.val$symbol %in% str_replace(gtf10kb.r.val2[i, "symbol"], "_RT", ""))
+
+ }
+
+
+ }
+
+ message("Export Extension Bed file ( 6 / 6 )")
+
+ gtf10kb.r.val2 <- rbind(gtf10kb.r.val2, gtf.r.val)
+ write_excel_csv(gtf10kb.r.val2, paste0(out, "GenesAndRT_", RT ,"bases_", suf ,".bed"),
+ delim = "\t", col_names = F, quote="none")
+
+ #return(list("Genes" = gtf.r.val, "RT" = gtf10kb.r.val2))
+}
+
+
+#################
+### __main__ ####
+#################
+
+gtfC <- gtfConvert(file = opt$file ,
+ out = opt$out ,
+ suf = opt$suffix ,
+ RT = opt$RT ,
+ chr = opt$chr
+)
+
+
diff --git a/src/.docker_modules/readthroughbincounts/0.1/src/trash_tests.R b/src/.docker_modules/readthroughbincounts/0.1/src/trash_tests.R
new file mode 100644
index 0000000000000000000000000000000000000000..c6babbf913a73855c9dee7232c1303a1c030ebf3
--- /dev/null
+++ b/src/.docker_modules/readthroughbincounts/0.1/src/trash_tests.R
@@ -0,0 +1,104 @@
+########################
+### 2023-07-31 #########
+### H. Polveche ########
+########################
+
+
+###################
+### trash tests ###
+###################
+
+
+library(tidyverse)
+
+exons <- read.csv2("../exons_genomiques_bis.csv", header = T)
+last_exons <- exons %>%
+ group_by(id_gene) %>%
+ dplyr::mutate(
+ first = dplyr::first(pos_sur_gene),
+ last = dplyr::last(pos_sur_gene)
+ ) %>%
+ filter(pos_sur_gene == last) %>%
+ select(id_gene, last, longueur) %>%
+ ungroup()
+
+
+inf50 <- last_exons %>%
+ filter(longueur < 50 )
+
+inf100 <- last_exons %>%
+ filter(longueur < 100 )
+
+resu <- last_exons %>%
+ summarise(mean=mean(longueur), sd = sd(longueur),
+ min = min(longueur), max= max(longueur))
+
+# commun_expression <- function(words){
+# ### words : string vector
+# ### find common expression
+#
+# words.split <- strsplit(words, '')
+# words.split <- lapply(words.split, `length<-`, max(nchar(words)))
+# words.mat <- do.call(rbind, words.split)
+# common.substr.length <- which.max(apply(words.mat, 2, function(col) !length(unique(col)) == 1)) - 1
+# reg.ex <- substr(words[1], 1, common.substr.length)
+#
+# return(reg.ex)
+# }
+
+# c("NCKAP5L_ENSG00000167566", "SH3TC1_ENSG00000125089", "NCS1_ENSG00000107130",
+# "RAB36_ENSG00000100228", "PPARD_ENSG00000112033", "FBLN1_ENSG00000077942")
+
+
+library(tidyverse)
+
+DEG.ctrl <- read.csv2("./results/siGL2/normcounts.csv", header = T)
+DEG.ctrl <- data.frame(ID=NA, DEG.ctrl)
+DEG.ctrl$ID <- rownames(DEG.ctrl)
+
+coldata.ctrl <- read.csv2("./results/siGL2/coldata.csv", header = T)
+rownames(coldata.ctrl) <- str_replace(rownames(coldata.ctrl), "-", ".")
+
+coldata.siDDX <- read.csv2("./results/siDDX/coldata.csv", header = T)
+coldata.siDDX$sampleName <- str_replace(coldata.siDDX$sampleName, "-", ".")
+
+DEG.siDDX <- read.csv2("./results/siDDX/normcounts.csv", header = T)
+DEG.siDDX <- data.frame(ID=NA, DEG.siDDX)
+DEG.siDDX$ID <- rownames(DEG.siDDX)
+
+DEG.siDDX.sum <- DEG.siDDX %>%
+ pivot_longer(!ID, names_to = "samples", values_to = "count") %>%
+ mutate(condition = if_else(str_ends(samples, "_RT"), "RT", "canonical")) %>%
+ group_by(condition, ID) %>%
+ summarise(mean = mean(count)) %>%
+ pivot_wider(names_from = c(condition), values_from = mean)
+
+DEG.ctrl.sum <- DEG.ctrl %>%
+ pivot_longer(!ID, names_to = "samples", values_to = "count") %>%
+ mutate(condition = if_else(str_ends(samples, "_RT"), "RT", "canonical")) %>%
+ group_by(condition, ID) %>%
+ summarise(mean = mean(count)) %>%
+ pivot_wider(names_from = c(condition), values_from = mean)
+
+
+#DEG.siDDX <- merge(DEG.siDDX, coldata.siDDX,
+# by.x = "samples", by.y = "sampleName", all.x = T)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+