# HG changeset patch
# User workflow4metabolomics
# Date 1562144894 14400
# Node ID b60dc620bd14d7944a465b52fa6a2f35a6f36ea6

planemo upload for repository https://github.com/workflow4metabolomics/metaMS commit 174a1713024f246c1485cbd75218577e89353522

diff -r 000000000000 -r b60dc620bd14 README.rst
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/README.rst	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,55 @@
+====================================
+GC-MS data processing version 2.1.1
+====================================
+
+1) Date : 2019-05-20
+
+2) Author and maintainer :
+
+   Yann GUITTON
+
+   LABERCA - PFCA Metabolomics Platform
+
+   E-mail: yann.guitton@oniris-nantes.fr / yann.guitton@gmail.com
+
+3) Funding :
+
+   Developed within IDEALG project (http://www.idealg.ueb.eu/versionAnglaise/)
+
+   Developed within IFB-MetaboHub W4M project
+
+4) Usage restrictions :
+
+   Use of this tool is restricted to the service conditions of the MetaboHUB-IFB infrastructures.
+   For any question regarding the use of these services, please contact: yann.guitton@oniris-nantes.fr
+
+5) Installation :
+
+   4 files are required for installation :
+
+   - 'README.rst'
+         Instructions for installation
+   
+   - 'metaMS_plot.xml'
+         Configuration file; to be put into the './galaxy-dist/tools/' directory 
+         and 2.png files for illustration
+
+   - 'metaMS_plot.r'
+         Wrapper code written in R aimed at launching the runGC function from the metaMS package given the arguments entered by the user through the Galaxy interface
+   
+   - 'metaMS R package '
+         The 'metaMS' package requires dependencies and can be installed with source("http://bioconductor.org/biocLite.R") or `biocLite("metaMS")`
+ 
+         This code is for installation of the Galaxy module on the Workflow4metabolomics.org MetaboHUB-IFB platform only and must not be distributed without the author agreement
+
+   
+Changelog/News
+--------------
+**Version 1.0 - 20/05/2019**
+
+- NEW : new tool extract from previous metaMS_runGC tool. EICs have been corrected.
+
+Test Status
+-----------
+
+Planemo test using conda: passed
diff -r 000000000000 -r b60dc620bd14 lib_metams.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/lib_metams.r	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,503 @@
+# lib_metams.r version 2.1.1
+# R function for metaMS runGC under W4M
+# author Yann GUITTON CNRS IRISA/LINA Idealg project 2014-2015
+# author Yann GUITTON Oniris Laberca 2015-2017
+
+
+#@author G. Le Corguille
+# This function will
+# - load the packages
+# - display the sessionInfo
+loadAndDisplayPackages <- function(pkgs) {
+    for(pkg in pkgs) suppressPackageStartupMessages( stopifnot( library(pkg, quietly=TRUE, logical.return=TRUE, character.only=TRUE)))
+
+    sessioninfo = sessionInfo()
+    cat(sessioninfo$R.version$version.string,"\n")
+    cat("Main packages:\n")
+    for (pkg in names(sessioninfo$otherPkgs)) { cat(paste(pkg,packageVersion(pkg)),"\t") }; cat("\n")
+    cat("Other loaded packages:\n")
+    for (pkg in names(sessioninfo$loadedOnly)) { cat(paste(pkg,packageVersion(pkg)),"\t") }; cat("\n")
+}
+
+#This function list the compatible files within the directory as xcms did
+#@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM
+getMSFiles <- function (directory) {
+    filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]","[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]")
+    filepattern <- paste(paste("\\.", filepattern, "$", sep=""),collapse="|")
+    info <- file.info(directory)
+    listed <- list.files(directory[info$isdir], pattern=filepattern,recursive=TRUE, full.names=TRUE)
+    files <- c(directory[!info$isdir], listed)
+    exists <- file.exists(files)
+    files <- files[exists]
+    return(files)
+}
+
+# This function retrieve a xset like object
+#@author Gildas Le Corguille lecorguille@sb-roscoff.fr
+getxcmsSetObject <- function(xobject) {
+    # XCMS 1.x
+    if (class(xobject) == "xcmsSet")
+        return (xobject)
+    # XCMS 3.x
+    if (class(xobject) == "XCMSnExp") {
+        # Get the legacy xcmsSet object
+        suppressWarnings(xset <- as(xobject, 'xcmsSet'))
+        if (!is.null(xset@phenoData$sample_group))
+            sampclass(xset) <- xset@phenoData$sample_group
+        else
+            sampclass(xset) <- "."
+        return (xset)
+    }
+}
+
+#J.Saint-Vanne
+#Function to correct the file names which can be written like "..alg8.mzData" and we just want "alg8"
+getCorrectFileName <- function(peaktable,sampleMetadata){
+
+    #Try to start for the first sample, avoid description of line with colnamesdontwant
+    i <- 1
+    while(!(sampleMetadata[1,1] %in% strsplit(colnames(peaktable)[i],"\\.")[[1]])) {
+        if(i < length(peaktable)) {
+            i <- i + 1
+        } else {
+            break
+        }
+    }
+    #i now correspond to the first column with a sample
+    for(j in 1:(nrow(sampleMetadata))) {
+        col <- j + i-1 #minus 1 cause i is the good column to start and j start at 1
+        if(col <= length(colnames(peaktable))) {
+            newname <- gsub("(^.*)(\\..*$)","\\1",colnames(peaktable)[col])
+            if(newname != sampleMetadata[j,1]){
+                #Correction for 2 points starting the name (I don't know why they are here...)
+                if(".." == gsub("(^\\.+)(.*)","\\1",newname)){
+                    newname <- sub("(^\\.+)(.*)","\\2",newname)
+                }
+            }
+            colnames(peaktable)[col] <- newname
+        }
+    }
+    return(peaktable)
+}
+
+
+#@author Gildas Le Corguille lecorguille@sb-roscoff.fr
+# This function get the raw file path from the arguments
+getRawfilePathFromArguments <- function(singlefile, zipfile, listArguments) {
+    if (!is.null(listArguments[["zipfile"]]))           zipfile = listArguments[["zipfile"]]
+    if (!is.null(listArguments[["zipfilePositive"]]))   zipfile = listArguments[["zipfilePositive"]]
+    if (!is.null(listArguments[["zipfileNegative"]]))   zipfile = listArguments[["zipfileNegative"]]
+
+    if (!is.null(listArguments[["singlefile_galaxyPath"]])) {
+        singlefile_galaxyPaths = listArguments[["singlefile_galaxyPath"]];
+        singlefile_sampleNames = listArguments[["singlefile_sampleName"]]
+    }
+    if (!is.null(listArguments[["singlefile_galaxyPathPositive"]])) {
+        singlefile_galaxyPaths = listArguments[["singlefile_galaxyPathPositive"]];
+        singlefile_sampleNames = listArguments[["singlefile_sampleNamePositive"]]
+    }
+    if (!is.null(listArguments[["singlefile_galaxyPathNegative"]])) {
+        singlefile_galaxyPaths = listArguments[["singlefile_galaxyPathNegative"]];
+        singlefile_sampleNames = listArguments[["singlefile_sampleNameNegative"]]
+    }
+    if (exists("singlefile_galaxyPaths")){
+        singlefile_galaxyPaths = unlist(strsplit(singlefile_galaxyPaths,","))
+        singlefile_sampleNames = unlist(strsplit(singlefile_sampleNames,","))
+
+        singlefile=NULL
+        for (singlefile_galaxyPath_i in seq(1:length(singlefile_galaxyPaths))) {
+            singlefile_galaxyPath=singlefile_galaxyPaths[singlefile_galaxyPath_i]
+            singlefile_sampleName=singlefile_sampleNames[singlefile_galaxyPath_i]
+            singlefile[[singlefile_sampleName]] = singlefile_galaxyPath
+        }
+    }
+    for (argument in c("zipfile","zipfilePositive","zipfileNegative","singlefile_galaxyPath","singlefile_sampleName","singlefile_galaxyPathPositive","singlefile_sampleNamePositive","singlefile_galaxyPathNegative","singlefile_sampleNameNegative")) {
+        listArguments[[argument]]=NULL
+    }
+    return(list(zipfile=zipfile, singlefile=singlefile, listArguments=listArguments))
+}
+
+
+#@author Gildas Le Corguille lecorguille@sb-roscoff.fr
+# This function retrieve the raw file in the working directory
+#   - if zipfile: unzip the file with its directory tree
+#   - if singlefiles: set symlink with the good filename
+retrieveRawfileInTheWorkingDirectory <- function(singlefile, zipfile) {
+    if(!is.null(singlefile) && (length("singlefile")>0)) {
+        for (singlefile_sampleName in names(singlefile)) {
+            singlefile_galaxyPath = singlefile[[singlefile_sampleName]]
+            if(!file.exists(singlefile_galaxyPath)){
+                error_message=paste("Cannot access the sample:",singlefile_sampleName,"located:",singlefile_galaxyPath,". Please, contact your administrator ... if you have one!")
+                print(error_message); stop(error_message)
+            }
+            file.symlink(singlefile_galaxyPath,singlefile_sampleName)
+        }
+        directory = "."
+    }
+    if(!is.null(zipfile) && (zipfile!="")) {
+        if(!file.exists(zipfile)){
+            error_message=paste("Cannot access the Zip file:",zipfile,". Please, contact your administrator ... if you have one!")
+            print(error_message)
+            stop(error_message)
+        }
+
+        #list all file in the zip file
+        #zip_files=unzip(zipfile,list=T)[,"Name"]
+
+        #unzip
+        suppressWarnings(unzip(zipfile, unzip="unzip"))
+
+        #get the directory name
+        filesInZip=unzip(zipfile, list=T);
+        directories=unique(unlist(lapply(strsplit(filesInZip$Name,"/"), function(x) x[1])));
+        directories=directories[!(directories %in% c("__MACOSX")) & file.info(directories)$isdir]
+        directory = "."
+        if (length(directories) == 1) directory = directories
+
+        cat("files_root_directory\t",directory,"\n")
+    }
+    return (directory)
+}
+
+##ADDITIONS FROM Y. Guitton
+getBPC <- function(file,rtcor=NULL, ...) {
+    object <- xcmsRaw(file)
+	sel <- profRange(object, ...)
+	cbind(if (is.null(rtcor)) object@scantime[sel$scanidx] else rtcor ,xcms:::colMax(object@env$profile[sel$massidx,sel$scanidx,drop=FALSE]))
+}
+
+getBPC2s <- function (files, xset = NULL, pdfname="BPCs.pdf", rt = c("raw","corrected"), scanrange=NULL) {
+    require(xcms)
+                   
+    #create sampleMetadata, get sampleMetadata and class
+    if(!is.null(xset)) {
+    	#When files come from XCMS3 directly before metaMS
+    	sampleMetadata <- xset@phenoData
+    } else {
+    	#When files come from a zip directory with raw files before metaMS
+	    sampleMetadata<-xcms:::phenoDataFromPaths(files)
+    }
+    class<-unique(sampleMetadata[,"class"]) #create phenoData like table
+    classnames<-vector("list",length(class))
+    for (i in 1:length(class)){
+        classnames[[i]]<-which( sampleMetadata[,"class"]==class[i])
+    }
+
+    N <- dim(sampleMetadata)[1]
+    TIC <- vector("list",N)
+
+    for (j in 1:N) {
+        TIC[[j]] <- getBPC(files[j])
+        #good for raw 
+        # seems strange for corrected
+        #errors if scanrange used in xcmsSetgeneration
+        if (!is.null(xcmsSet) && rt == "corrected"){
+            rtcor <- xcmsSet@rt$corrected[[j]] 
+        }else{
+            rtcor <- NULL
+        }
+        TIC[[j]] <- getBPC(files[j],rtcor=rtcor)
+    }
+
+    pdf(pdfname,w=16,h=10)
+    cols <- rainbow(N)
+    lty = 1:N
+    pch = 1:N
+    #search for max x and max y in BPCs
+    xlim = range(sapply(TIC, function(x) range(x[,1])))
+    ylim = range(sapply(TIC, function(x) range(x[,2])))
+    ylim = c(-ylim[2], ylim[2])
+
+    ##plot start
+    if (length(class)>2){
+        for (k in 1:(length(class)-1)){
+            for (l in (k+1):length(class)){
+                cat(paste(class[k],"vs",class[l],sep=" ","\n")) 
+                plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k]," vs ",class[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
+                colvect<-NULL
+                for (j in 1:length(classnames[[k]])) {
+                    tic <- TIC[[classnames[[k]][j]]]
+                    # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
+                    points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+                    colvect<-append(colvect,cols[classnames[[k]][j]])
+                }
+                for (j in 1:length(classnames[[l]])) {
+                    # i=class2names[j]
+                    tic <- TIC[[classnames[[l]][j]]]
+                    points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
+                    colvect<-append(colvect,cols[classnames[[l]][j]])
+                }
+                legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]],classnames[[l]])]))), col = colvect, lty = lty, pch = pch)
+            }
+        }
+    }#end if length >2
+
+    if (length(class)==2){
+        k=1
+		l=2
+        colvect<-NULL
+        plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k],"vs",class[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
+
+        for (j in 1:length(classnames[[k]])) {
+            tic <- TIC[[classnames[[k]][j]]]
+            # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
+            points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+            colvect<-append(colvect,cols[classnames[[k]][j]])
+        }
+        for (j in 1:length(classnames[[l]])) {
+            # i=class2names[j]
+            tic <- TIC[[classnames[[l]][j]]]
+            points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
+            colvect<-append(colvect,cols[classnames[[l]][j]])
+        }
+        legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]],classnames[[l]])]))), col = colvect, lty = lty, pch = pch)
+    }#end length ==2
+    
+    if (length(class)==1){
+        k=1
+		ylim = range(sapply(TIC, function(x) range(x[,2])))
+        colvect<-NULL
+        plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
+
+        for (j in 1:length(classnames[[k]])) {
+            tic <- TIC[[classnames[[k]][j]]]
+            # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
+            points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+            colvect<-append(colvect,cols[classnames[[k]][j]])
+        }
+        legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]])]))), col = colvect, lty = lty, pch = pch)
+    }#end length ==1
+    dev.off()
+}
+
+getTIC <- function(file,rtcor=NULL) {
+    object <- xcmsRaw(file)
+    cbind(if (is.null(rtcor)) object@scantime else rtcor, rawEIC(object,mzrange=range(object@env$mz))$intensity)
+}
+
+##  overlay TIC from all files in current folder or from xcmsSet, create pdf
+getTIC2s <- function(files, xset=NULL, pdfname="TICs.pdf", rt=c("raw","corrected")) {
+    require(xcms)
+
+    #create sampleMetadata, get sampleMetadata and class
+    if(!is.null(xset)){
+		#When files come from XCMS3 before metaMS treatment
+    	sampleMetadata<-xset@phenoData
+    } else {
+		#When files come from a zip directory with raw files before metaMS
+    	sampleMetadata<-xcms:::phenoDataFromPaths(files)
+    }
+    class<-as.vector(levels(sampleMetadata[,"class"])) #create phenoData like table
+    classnames<-vector("list",length(class))
+    for (i in 1:length(class)){
+        classnames[[i]]<-which( sampleMetadata[,"class"]==class[i])
+    }
+        
+    N <- dim(sampleMetadata)[1]
+    TIC <- vector("list",N)
+
+    for (i in 1:N) {
+        cat(files[i],"\n")
+        if (!is.null(xcmsSet) && rt == "corrected")
+            rtcor <- xcmsSet@rt$corrected[[i]]
+        else
+            rtcor <- NULL
+        TIC[[i]] <- getTIC(files[i],rtcor=rtcor)
+    }
+ 
+    pdf(pdfname,w=16,h=10)
+    cols <- rainbow(N)
+    lty = 1:N
+    pch = 1:N
+    #search for max x and max y in TICs
+    xlim = range(sapply(TIC, function(x) range(x[,1])))
+    ylim = range(sapply(TIC, function(x) range(x[,2])))
+    ylim = c(-ylim[2], ylim[2])  
+	  
+    ##plot start
+    if (length(class)>2){
+        for (k in 1:(length(class)-1)){
+            for (l in (k+1):length(class)){
+                print(paste(class[k],"vs",class[l],sep=" ")) 
+                plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",class[k]," vs ",class[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
+                colvect<-NULL
+                for (j in 1:length(classnames[[k]])) {
+                    tic <- TIC[[classnames[[k]][j]]]
+                    # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
+                    points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+                    colvect<-append(colvect,cols[classnames[[k]][j]])
+                }
+                for (j in 1:length(classnames[[l]])) {
+                    # i=class2names[j]
+                    tic <- TIC[[classnames[[l]][j]]]
+                    points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
+                    colvect<-append(colvect,cols[classnames[[l]][j]])
+                }
+                legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]],classnames[[l]])]))), col = colvect, lty = lty, pch = pch)
+            }
+        }
+    }#end if length >2
+
+    if (length(class)==2){
+        k=1
+        l=2
+        plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",class[k],"vs",class[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
+        colvect<-NULL
+        for (j in 1:length(classnames[[k]])) {
+            tic <- TIC[[classnames[[k]][j]]]
+            # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
+            points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+            colvect<-append(colvect,cols[classnames[[k]][j]])
+        }
+        for (j in 1:length(classnames[[l]])) {
+            # i=class2names[j]
+            tic <- TIC[[classnames[[l]][j]]]
+            points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
+            colvect<-append(colvect,cols[classnames[[l]][j]])
+        }
+        legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]],classnames[[l]])]))), col = colvect, lty = lty, pch = pch)
+    }#end length ==2
+
+    if (length(class)==1){
+        k=1
+        ylim = range(sapply(TIC, function(x) range(x[,2])))
+        plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",class[k], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
+        colvect<-NULL
+        for (j in 1:length(classnames[[k]])) {
+            tic <- TIC[[classnames[[k]][j]]]
+            # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
+            points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
+            colvect<-append(colvect,cols[classnames[[k]][j]])
+        }
+        legend("topright",paste(gsub("(^.+)\\..*$","\\1",basename(files[c(classnames[[k]])]))), col = colvect, lty = lty, pch = pch)
+    }#end length ==1
+    dev.off()
+}
+
+
+#Update by J.Saint-Vanne
+##addition for quality control of peak picking
+#metaMS EIC and pspectra plotting option
+#version 20190520
+#only for Galaxy 
+plotUnknowns<-function(resGC, unkn="", DB=NULL, fileFrom=NULL){
+
+    ##Annotation table each value is a pcgrp associated to the unknown 
+    ##NOTE pcgrp index are different between xcmsSet and resGC due to filtering steps in metaMS
+    ##R. Wehrens give me some clues on that and we found a correction
+    
+	#correction of annotation matrix due to pcgrp removal by quality check in runGCresult
+	#matrix of correspondance between an@pspectra and filtered pspectra from runGC
+    #Select only pspectra which correpond to them select in metaMS
+    # col1 = filtered spectra from runGC and col2 = an@spectra
+	allPCGRPs <-lapply(1:length(resGC$xset),
+				function(i) {
+					an <- resGC$xset[[i]]
+					huhn <- an@pspectra[which(sapply(an@pspectra, length) >=
+					metaSetting(resGC$settings,
+					"DBconstruction.minfeat"))]
+					matCORR<-cbind(1:length(huhn), match(huhn, an@pspectra))
+				})
+    #Build a new annotation list with sampnames and pseudospectra number from xset
+    helpannotation <- list()
+    for(j in 1:length(resGC$xset)){
+        helpannotation[[j]] <- resGC$annotation[[j]][1:2]
+        pspvector <- vector()
+        for(i in 1: nrow(helpannotation[[j]])){
+            #Find corresponding pspec
+            psplink <- allPCGRPs[[j]][match(helpannotation[[j]][i,1],allPCGRPs[[j]]),2]
+            pspvector <- c(pspvector,psplink)
+            #Change the annotation column into sampname column
+            if(helpannotation[[j]][i,2] < 0){
+                #It's an unknown
+                new_name <- paste("Unknown",abs(as.integer(helpannotation[[j]][i,2])))
+                helpannotation[[j]][i,2] <- new_name
+            }else{
+                #It has been found in local database
+                for(k in 1:length(DB)){
+                    if(helpannotation[[j]][i,2] == k){
+                        helpannotation[[j]][i,2] <- DB[[k]]$Name
+                        break
+                    }
+                }
+            }
+        }
+        helpannotation[[j]] <- cbind(helpannotation[[j]],pspvector)
+        names(helpannotation)[j] <- names(resGC$annotation[j])
+    }
+    peaktable <- resGC$PeakTable
+		
+	par (mar=c(5, 4, 4, 2) + 0.1)
+	#For each unknown
+	for (l in 1:length(unkn)){
+		#recordPlot
+		perpage=3 #if change change layout also!
+		dev.new(width=21/2.54, height=29.7/2.54, file=paste("Unknown_",unkn[l],".pdf", sep="")) #A4 pdf
+		# par(mfrow=c(perpage,2))
+		layout(matrix(c(1,1,2,3,4,4,5,6,7,7,8,9), 6, 2, byrow = TRUE), widths=rep(c(1,1),perpage), heights=rep(c(1,5),perpage))
+		# layout.show(6)
+		oma.saved <- par("oma")
+		par(oma = rep.int(0, 4))
+		par(oma = oma.saved)
+		o.par <- par(mar = rep.int(0, 4))
+		on.exit(par(o.par))
+		#For each sample
+		for (c in 1:length(resGC$xset)) {	
+			#get sample name
+			sampname<-basename(resGC$xset[[c]]@xcmsSet@filepaths)
+			#remove .cdf, .mzXML filepattern
+			filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", 
+									"[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]")
+			filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|")
+			sampname<-gsub(filepattern, "",sampname)					 
+			title1<-paste(peaktable[unkn[l],1],"from",sampname, sep = " ")
+			an<-resGC$xset[[c]]
+    		if(fileFrom == "zipfile") {
+				an@xcmsSet@filepaths <- paste0("./",an@xcmsSet@phenoData[,"class"],"/",basename(an@xcmsSet@filepaths))
+				}#else {
+        			#print(an@xcmsSet@filepaths)
+					#an@xcmsSet@filepaths <- paste0("./",basename(an@xcmsSet@filepaths))
+				#}
+			#Find the good annotation for this sample
+            for(a in 1:length(helpannotation)){    
+                if(gsub(filepattern, "", names(helpannotation)[a]) == paste0("./",sampname)){
+                    #Find the unkn or the matched std in this sample
+                    findunkn <- FALSE
+                    for(r in 1:nrow(helpannotation[[a]])){
+                        if(helpannotation[[a]][r,"annotation"] == peaktable[unkn[l],1]){
+                            findunkn <- TRUE
+                            pcgrp <- helpannotation[[a]][r,"pspvector"]
+							par (mar=c(0, 0, 0, 0) + 0.1)
+							#Write title
+							plot.new()
+							box()
+							text(0.5, 0.5, title1, cex=2)						
+							par (mar=c(3, 2.5, 3, 1.5) + 0.1)
+							#Window for EIC
+							plotEICs(an, pspec=pcgrp, maxlabel=2)
+							#Window for pseudospectra
+							plotPsSpectrum(an, pspec=pcgrp, maxlabel=2)
+						}
+					}
+					if(!findunkn) {
+						par (mar=c(0, 0, 0, 0) + 0.1)
+                   		#Write title
+						plot.new()
+						box()
+						text(0.5, 0.5, title1, cex=2)
+                   		#Window for EIC
+                   		plot.new()
+                   		box()
+						text(0.5, 0.5, "NOT FOUND", cex=2)
+						#Window for pseudospectra
+						plot.new()
+						box()
+						text(0.5, 0.5, "NOT FOUND", cex=2)
+					}
+					break
+				}
+    		}
+		}
+		graphics.off()
+	}#end  for unkn[l]
+}#end function
\ No newline at end of file
diff -r 000000000000 -r b60dc620bd14 macros.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,78 @@
+<?xml version="1.0"?>
+
+<macros>
+
+	<xml name="stdio">
+        <stdio>
+            <exit_code range="1" level="fatal" />
+        </stdio>
+	</xml>
+
+    <xml name="requirements">
+        <requirements>
+            <requirement type="package" version="1.18.1">bioconductor-metams</requirement>
+            <requirement type="package" version="1.1_4">r-batch</requirement>
+            <yield />
+        </requirements>
+    </xml>
+
+	<xml name="input_file_load">
+        <section name="file_load_section" title="Resubmit your raw dataset or your zip file">
+            <conditional name="file_load_conditional">
+                <param name="file_load_select" type="select" label="Resubmit your dataset or your zip file" help="Use only if you get a message saying that your original dataset or zip file have been deleted on the server." >
+                    <option value="no" >no need</option>
+                    <option value="yes" >yes</option>
+                </param>
+                <when value="no">
+                </when>
+                <when value="yes">
+                    <param name="input" type="data" format="mzxml,mzml,mzdata,netcdf,no_unzip.zip,zip" multiple="true" label="File(s) from your history containing your chromatograms" help="Single file mode for the format: mzxml, mzml, mzdata and netcdf. Zip file mode for the format: no_unzip.zip, zip. See the help section below." />
+                </when>
+            </conditional>
+        </section>
+	</xml>
+
+	<!--<xml name="test_file_load_alg">
+        <section name="file_load_section">
+            <conditional name="file_load_conditional">
+                <param name="file_load_select" value="yes" />
+                <param name="input" value="RawFilesTest_alg2_t.mzData,RawFilesTest_alg3_t.mzData,RawFilesTest_alg7_t.mzData,RawFilesTest_alg8_t.mzData,RawFilesTest_alg9_t.mzData,RawFilesTest_alg11_t.mzData" ftype="mzdata" />
+            </conditional>
+        </section>
+	</xml>-->
+
+	<xml name="test_file_load_alg_symlink">
+        <section name="file_load_section">
+            <conditional name="file_load_conditional">
+                <param name="file_load_select" value="yes" />
+                <param name="input" value="alg2.mzData,alg3.mzData,alg7.mzData,alg8.mzData,alg9.mzData,alg11.mzData" ftype="mzdata" />
+            </conditional>
+        </section>
+	</xml>
+
+    <!-- COMMAND -->
+    <token name="@COMMAND_RSCRIPT@">LC_ALL=C Rscript $__tool_directory__/</token>
+
+    <token name="@COMMAND_LOG_EXIT@">
+        ;
+        return=\$?;
+        cat 'log.txt';
+        sh -c "exit \$return"
+    </token>
+
+    <!-- FILE_LOAD for planemo test -->
+    <!-- Change | for , because I use it in metaMS tool -->
+    <token name="@COMMAND_FILE_LOAD@">
+        #if $file_load_section.file_load_conditional.file_load_select == "yes":
+            #if $file_load_section.file_load_conditional.input[0].is_of_type("mzxml") or $file_load_section.file_load_conditional.input[0].is_of_type("mzml") or $file_load_section.file_load_conditional.input[0].is_of_type("mzdata") or $file_load_section.file_load_conditional.input[0].is_of_type("netcdf"):
+                #set singlefile_galaxyPath = ','.join( [ str( $single_file ) for $single_file in $file_load_section.file_load_conditional.input ] )
+                #set singlefile_sampleName = ','.join( [ str( $single_file.name ) for $single_file in $file_load_section.file_load_conditional.input ] )
+
+                singlefile_galaxyPath '$singlefile_galaxyPath' singlefile_sampleName '$singlefile_sampleName'
+            #else
+                zipfile '$file_load_section.file_load_conditional.input'
+            #end if
+        #end if
+	</token>
+
+</macros>
\ No newline at end of file
diff -r 000000000000 -r b60dc620bd14 metaMS_plot.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/metaMS_plot.r	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,152 @@
+#!/usr/bin/env Rscript
+# metaMS_plot.r version="1.0.0"
+#created by Yann GUITTON and updated by Julien SAINT-VANNE
+
+
+# ----- LOG FILE -----
+#log_file <- file("log.txt", open = "wt")
+#sink(log_file)
+#sink(log_file, type = "output")
+
+
+# ----- PACKAGE -----
+cat("\tSESSION INFO\n")
+
+#Import the different functions
+source_local <- function(fname) {
+    argv <- commandArgs(trailingOnly = FALSE)
+    base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
+    source(paste(base_dir, fname, sep="/"))
+}
+source_local("lib_metams.r")
+
+pkgs <- c("metaMS","batch") #"batch" necessary for parseCommandArgs function
+loadAndDisplayPackages(pkgs)
+
+cat("\n")
+
+modNamC <- "plot_metaMS" ## module name
+
+cat("\nStart of the '", modNamC, "' Galaxy module call: ", format(Sys.time(), "%a %d %b %Y %X"), "\n\n", sep="")
+
+
+# ----- ARGUMENTS -----
+cat("\tARGUMENTS INFO\n\n")
+args = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects
+#write.table(as.matrix(args), col.names=F, quote=F, sep='\t\t')
+print(cbind(value = unlist(args)))
+
+
+# ----- PROCESSING INFILE -----
+cat("\n\n\tARGUMENTS PROCESSING INFO\n\n")
+
+# Loading RData file
+load(args$metaMS)
+if (!exists("resGC")) stop("\n\nERROR: The RData doesn't contain any object called 'resGC' which is provided by the tool: new_metaMS.runGC")
+
+if(args$selecteic) {
+    #Unknown EIC parameter
+    if (args$unkn[1] != "NULL") {
+        #When unkn = 0 user want to process all unknowns
+        if(args$unkn[1] == 0) {
+            args$unkn <- c(1:nrow(resGC$PeakTable))
+            print("User want to process on all unknown(s) found in metaMS process")
+        }
+        #TODO find the biggest number of unkn ask by user cause it can write "1,15,9,8" with a max of 11 unkn. With this code it finds the 8 and it will pass
+        #Verify that there is not more user's unkn than metaMS unkn (find in resGC$PeakTable)
+        cat("Number of unknown after metaMS process :",nrow(resGC$PeakTable),"\n")
+        cat("Number of the last unknown ask by user :",args$unkn[length(args$unkn)],"\n")
+        cat("Number of unknown ask by user :",length(args$unkn),"\n")
+        if(args$unkn[length(args$unkn)] <= nrow(resGC$PeakTable)) {
+            unknarg <- args$unkn
+        } else {
+            error_message="Too much unkn compare metaMS results"
+            print(error_message)
+            stop(error_message)
+        }
+    } else {
+        error_message <- "No EIC selected !"
+        print(error_message)
+        stop(error_message)
+    }
+}
+
+cat("\n\n")
+
+
+# ----- INFILE PROCESSING -----
+cat("\tINFILE PROCESSING INFO\n\n")
+
+# Handle infiles
+if (!exists("singlefile")) singlefile <- NULL
+if (!exists("zipfile")) zipfile <- NULL
+rawFilePath <- getRawfilePathFromArguments(singlefile, zipfile, args)
+zipfile <- rawFilePath$zipfile
+singlefile <- rawFilePath$singlefile
+directory <- retrieveRawfileInTheWorkingDirectory(singlefile, zipfile)
+
+
+# ----- MAIN PROCESSING INFO -----
+cat("\n\n\tMAIN PROCESSING INFO\n")
+
+
+cat("\t\tCOMPUTE\n")
+
+#Use getTIC2s and getBPC2s because getTICs and getBPCs can exists due to transfert of function in Rdata
+
+if(!is.null(singlefile)) {
+    files <- paste("./",names(singlefile),sep="")
+    if(!is.null(files)){
+        if(args$selectbpc){
+            cat("\n\tProcessing BPC(s) from XCMS files...\n")
+            c <- getBPC2s(files = files, xset = xset, rt="raw", pdfname="BPCs_raw.pdf")
+            cat("BPC(s) created...\n")
+        }
+        if(args$selecttic){
+            cat("\n\tProcessing TIC(s) from XCMS files...\n")
+            b <- getTIC2s(files = files, xset = xset, rt="raw", pdfname="TICs_raw.pdf")
+            cat("TIC(s) created...\n")
+        }
+        if(args$selecteic){
+            cat("\n\tProcessing EIC(s) from XCMS files...\n")
+            cat(length(unknarg),"unknown(s) will be process !\n")
+            plotUnknowns(resGC=resGC, unkn=unknarg, DB=DBgc, fileFrom="singlefile")
+            cat("EIC(s) created...\n")
+            #Merge pdf
+            system(paste('gs  -o GCMS_EIC.pdf  -sDEVICE=pdfwrite  -dPDFSETTINGS=/prepress  Unknown_*.pdf'))
+        }
+    } else {
+        error_message <- paste("Can't find",files,"!")
+        print(error_message)
+        stop(error_message)
+    }
+}
+if(!is.null(zipfile)) {
+    files <- getMSFiles(directory)
+    if(!is.null(files)) {
+        if(args$selectbpc) {
+            cat("\n\tProcessing BPC(s) from raw files...\n")
+            c <- getBPC2s(files = files, rt="raw", pdfname="BPCs_raw.pdf")
+            cat("BPC(s) created...\n")
+        }
+        if(args$selecttic) {
+            cat("\n\tProcessing TIC(s) from raw files...\n")
+            b <- getTIC2s(files = files, rt="raw", pdfname="TICs_raw.pdf")  
+            cat("TIC(s) created...\n")
+        }
+        if(args$selecteic) {
+            cat("\n\tProcessing EIC(s) from XCMS files...\n")
+            cat(length(unknarg),"unknown(s) will be process !\n")
+            plotUnknowns(resGC=resGC, unkn=unknarg, DB=DBgc, fileFrom="zipfile")
+            cat("EIC(s) created...\n")
+            #Merge pdf
+            system(paste('gs -sOutputFile=GCMS_EIC.pdf -sDEVICE=pdfwrite -dPDFSETTINGS=/prepress Unknown_*.pdf'))
+        }
+    } else {
+        error_message <- paste("Can't find",files,"!")
+        print(error_message)
+        stop(error_message)
+    } 
+}
+
+cat("\nEnd of '", modNamC, "' Galaxy module call: ", as.character(Sys.time()), "\n", sep = "")
\ No newline at end of file
diff -r 000000000000 -r b60dc620bd14 metaMS_plot.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/metaMS_plot.xml	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,266 @@
+ <tool id="metams_plot" name="metaMS.plot" version="1.0.0">
+
+    <description>GC-MS data preprocessing using metaMS package</description>
+
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    
+    <expand macro="requirements">
+        <requirement type="package" version="9.22">ghostscript</requirement>
+    </expand>
+    <expand macro="stdio"/>
+
+    <command><![CDATA[
+    @COMMAND_RSCRIPT@/metaMS_plot.r
+        
+        metaMS '$metaMS'
+
+        selecttic $selectedtic
+
+        selectbpc $selectedbpc
+
+        selecteic $selectedeic.EIC
+        
+        #if $selectedeic.EIC == "true"
+            unkn "c($selectedeic.unkn)"
+        #else
+            unkn "none"
+        #end if
+
+        @COMMAND_FILE_LOAD@
+
+    ]]></command>
+
+    <inputs>
+
+        <param name="metaMS" type="data" format="rdata" label="Rdata from new_metaMS_runGC" help="Rdata file containing a metaMS preprocess object" />
+        <param name="selectedtic" type="boolean" checked="false" falsevalue="false" truevalue="true" label="Do you want to process for TIC(s) ?" />
+        <param name="selectedbpc" checked="false" falsevalue="false" truevalue="true" label="Do you want to process for BPC(s) ?"  type="boolean" />
+
+        <conditional name="selectedeic">
+            <param name="EIC" checked="false" falsevalue="false" truevalue="true" label="Do you want to process for EIC(s) ?"  type="boolean">
+                <option value="false">no</option>
+                <option value="true">yes</option>
+            </param>
+            <when value="true">
+                <param name="unkn" type="text" value="1:5" label="EIC_Unknown" help="vector of peaks number to be plotted, for example 1:5 (mean 1 to 5) or 1,4,12  (means 1 4 and 12). For all EIC use 0" /> 
+            </when>
+            <when value="false"/>
+        </conditional>
+
+        <expand macro="input_file_load"/>
+
+    </inputs>
+
+    <outputs>
+    
+        <!-- Only when user selected TIC option -->
+        <data name="ticsRawPdf"   format="pdf" from_work_dir="TICs_raw.pdf" label="TICs_raw.pdf">
+            <filter>selectedtic is True</filter>
+        </data>
+        <!-- Only when user selected BPC option -->
+        <data name="bpcsRawPdf"   format="pdf" from_work_dir="BPCs_raw.pdf" label="BPCs_raw.pdf">
+            <filter>selectedbpc is True</filter>
+        </data>
+        <!-- Only when user selected EIC option -->
+        <data name="unknownPdf"   format="pdf" from_work_dir="GCMS_EIC.pdf" label="GCMS_EIC.pdf">
+            <filter>selectedeic['EIC'] is True</filter>
+        </data>
+
+    </outputs>
+
+    <tests>
+
+        <!-- Test TIC -->
+        <test>
+            <param name="metaMS" value="runGC_test.RData"  ftype="rdata" />
+            <expand macro="test_file_load_alg_symlink" />
+            <param name="selectedtic" value="true"/>
+            <output name="ticsRawPdf" value="TICs_raw.pdf" ftype="pdf" compare="sim_size" delta="600"/>
+        </test>
+        <!-- Test BPC -->
+        <test>
+            <param name="metaMS" value="runGC_noDB.RData"  ftype="rdata" />
+            <expand macro="test_file_load_alg_symlink" />
+            <param name="selectedbpc" value="true"/>
+            <output name="bpcsRawPdf" value="BPCs_raw.pdf" ftype="pdf" compare="sim_size" delta="2000"/>
+        </test>
+        <!-- Test EICs -->
+        <test>
+            <param name="metaMS" value="runGC_noDB.RData"  ftype="rdata" />
+            <expand macro="test_file_load_alg_symlink" />
+            <conditional name="selectedeic">
+                <param name="EIC" value="true"/>
+                <param name="unkn" value="1:5"/>
+            </conditional>
+            <output name="unknownPdf" value="GCMS_EIC_noDB.pdf" ftype="pdf" compare="sim_size" delta="1200"/>
+        </test>
+
+        <!-- Tests with DB comparison -->
+        <!-- Test TIC -->
+        <!--<test>
+            <param name="metaMS" value="runGC.RData"  ftype="rdata" />
+            <param name="selectedtic|TIC" value="true"/>
+            <output name="ticsRawPdf" value="TICs_raw.pdf" ftype="pdf" compare="sim_size" delta="600"/>
+        </test>
+        --><!-- Test BPC -->
+        <!--<test>
+            <param name="metaMS" value="runGC.RData"  ftype="rdata" />
+            <param name="selectedbpc|BPC" value="true"/>
+            <output name="bpcsRawPdf" value="BPCs_raw.pdf" ftype="pdf" compare="sim_size" delta="600"/>
+        </test>
+        --><!-- Test EICs -->
+        <!--<test>
+            <param name="metaMS" value="runGC.RData"  ftype="rdata" />
+            <param name="selectedeic|EIC" value="true"/>
+            <output name="unknownPdf" value="GCMS_EIC.pdf" ftype="pdf" compare="sim_size" delta="600"/>
+        </test>
+-->
+    </tests>
+    
+    <help>
+
+<!--
+TODO : Add test on EICs (problem with gs not found whereas I added pip install ghostscript and bgs in .travis.yml)
+-->
+
+.. class:: infomark
+
+**Author(s)**  Ron Wehrens (ron.wehrens@gmail.com), Georg Weingart, Fulvio Mattivi
+
+.. class:: infomark
+
+**Galaxy wrapper and scripts developpers** Guitton Yann LABERCA yann.guitton@oniris-nantes.fr and Saint-Vanne Julien julien.saint-vanne@sb-roscoff.fr
+
+.. class:: infomark
+
+**Please cites**  
+ 
+ metaMS : Wehrens, R.; Weingart, G.; Mattivi, F. Journal of Chromatography B.
+
+ xcms :   Smith, C. A.; Want, E. J.; O’Maille, G.; Abagyan, R.; Siuzdak, G. Anal. Chem. 2006, 78, 779–787.
+
+
+---------------------------------------------------
+
+====================
+metaMS_plot
+====================
+------------
+Description
+------------
+
+This tool will plot Base Peak Intensity chromatogram (BPI) and Total Ion Current chromatogram (TIC) from xcms experiments.
+
+It will compare with opposite graphs your different classes given by a samplemetadata file or from xcms.findchrompeaks Merger tool.
+
+It can also make EICs from your unknowns that you choose, with their pseudospectra.
+  
+
+-----------------
+Workflow position
+-----------------
+
+
+**Upstream tools**
+
+You must use result file from :
+
+========================= ==================== ======= ==========
+Name                      output file          format  parameter
+========================= ==================== ======= ==========
+metaMS_runGC              runGC.RData           RData   file                     
+========================= ==================== ======= ==========
+
+
+
+**General schema of the metabolomic workflow for GCMS**
+
+.. image:: workflow_metaMS_plot.png
+
+-----------
+Input files
+-----------
+
+This tool always take files output from metaMS_runGC
+
++---------------------------+------------+
+| Parameter : num + label   |   Format   |
++===========================+============+
+| 1 : RData file            |   RData    |
++---------------------------+------------+
+
+
+----------
+Parameters
+----------
+
+There is no specific parameters except the choice for your EICs.
+
+----------
+Outputs
+----------
+
+According to your choice(s), you can have different output(s) :
+
+- The output file **BPCs_raw.pdf** is a pdf file where each page contain BPC of a class opposed to an other class.
+- The output file **TICs_raw.pdf** is a pdf file where each page contain TIC of a class opposed to an other class.
+- The output file **GCMS_EIC.pdf** is a pdf file where pages contain EICs from each sample for each unknown of your choice.
+
+
+----------------
+Working Example
+----------------
+.. class:: warningmark  
+
+**Reference Data for testing are taken from:**
+
+Dittami,S.M. et al. (2012) *Towards deciphering dynamic changes and evolutionary mechanisms involved in the adaptation to low salinities in Ectocarpus (brown algae): Adaptation to low salinities in Ectocarpus.* The Plant Journal
+
+Input files
+-----------
+
+    | **RData file** -> runGC_test.RData
+
+Parameters
+----------
+
+    | TIC -> **TRUE**
+    | BPC -> **TRUE**
+    | EIC -> **TRUE**
+        | Unkn -> **1-5**
+
+
+Output files
+------------
+
+    | **1) TICs_raw.pdf (Total Ion Chromatogram) :**
+
+    .. image:: BPCs_raw.pdf
+
+    | **2) BPCs_raw.pdf (Base Peak Chromatograms) :**
+
+    .. image:: TICs_raw.pdf
+
+    | **3) GCMS_EIC.pdf (Extracted Ion Chromatogram) :**
+
+    .. image:: GCMS_EIC.pdf
+
+
+---------------------------------------------------
+
+Changelog/News
+--------------
+**Version 1.0 - 20/05/2019**
+
+- NEW: new tool extract from previous metaMS_runGC tool
+
+    </help>
+
+    <citations>
+        <citation type="doi">10.1016/j.jchromb.2014.02.051</citation>
+        <citation type="doi">10.1093/bioinformatics/btu813</citation>
+    </citations>
+
+</tool>
\ No newline at end of file
diff -r 000000000000 -r b60dc620bd14 static/images/workflow_metaMS_plot.graphml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/static/images/workflow_metaMS_plot.graphml	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,2070 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
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+                <y:LabelModel>
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+                </y:ModelParameter>
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+              <y:StyleProperties>
+                <y:Property class="java.lang.Boolean" name="y.view.ShadowNodePainter.SHADOW_PAINTING" value="false"/>
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+              </y:StyleProperties>
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+              <y:Fill hasColor="false" transparent="false"/>
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+              <y:StyleProperties>
+                <y:Property class="java.lang.Integer" name="com.yworks.sbgn.style.radius" value="10"/>
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+            <y:GenericNode configuration="com.yworks.sbgn.Macromolecule">
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diff -r 000000000000 -r b60dc620bd14 test-data/alg2.mzData
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/alg2.mzData	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,26991 @@
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diff -r 000000000000 -r b60dc620bd14 test-data/alg3.mzData
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/alg3.mzData	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,26991 @@
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diff -r 000000000000 -r b60dc620bd14 test-data/alg7.mzData
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/alg7.mzData	Wed Jul 03 05:08:14 2019 -0400
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diff -r 000000000000 -r b60dc620bd14 test-data/alg8.mzData
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/alg8.mzData	Wed Jul 03 05:08:14 2019 -0400
@@ -0,0 +1,26991 @@
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diff -r 000000000000 -r b60dc620bd14 test-data/alg9.mzData
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/alg9.mzData	Wed Jul 03 05:08:14 2019 -0400
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diff -r 000000000000 -r b60dc620bd14 test-data/runGC.RData
Binary file test-data/runGC.RData has changed
diff -r 000000000000 -r b60dc620bd14 test-data/runGC_noDB.RData
Binary file test-data/runGC_noDB.RData has changed
diff -r 000000000000 -r b60dc620bd14 test-data/runGC_test.RData
Binary file test-data/runGC_test.RData has changed