# HG changeset patch # User melpetera # Date 1539251249 14400 # Node ID b7a6a88f518ab26efe2d12a4c1e7534c1a729f1f Uploaded diff -r 000000000000 -r b7a6a88f518a IDchoice/.shed.yml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/.shed.yml Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,6 @@ +categories: [Metabolomics] +description: '[W4M][Utils] Choosing new identifiers.' +homepage_url: http://workflow4metabolomics.org +long_description: 'Available for the W4M project: http://workflow4metabolomics.org / This tool is designed to make you choose a particular column in your metadata file to be considered as identifiers for your W4M-3-tables-format data.' +name: idchoice +owner: melpetera diff -r 000000000000 -r b7a6a88f518a IDchoice/.travis.yml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/.travis.yml Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,19 @@ +# This is a special configuration file to run tests on Travis-CI via +# GitHub notifications when changes are committed. +# +# See http://travis-ci.org/ for details +language: python + +before_install: + - sudo apt-get install -y python-virtualenv + - virtualenv planemo-venv + - . planemo-venv/bin/activate + - pip install --upgrade pip setuptools + - pip install planemo + - planemo conda_init + +install: + - planemo conda_install ${TRAVIS_BUILD_DIR} + +script: +- planemo test --install_galaxy --no_cache_galaxy --conda_dependency_resolution ${TRAVIS_BUILD_DIR} \ No newline at end of file diff -r 000000000000 -r b7a6a88f518a IDchoice/IDchoice.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/IDchoice.xml Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,159 @@ + + Choosing a particular column in your metadata to be considered as Identifiers + + r-batch + + + IDchoice_wrap.R + dataMatrix_in "$dataMatrix_in" + Metadata_in "$Metadata_in" + + metatype "$metatype" + col_name "$col_name" + makeunique "$makeunique" + + DM_out "$DM_out" + meta_out "$meta_out" + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +.. class:: infomark + +**Authors** + | Melanie Petera - PFEM ; INRA ; MetaboHUB + +--------------------------------------------------- + +======================== +ID Choice +======================== + +----------- +Description +----------- + +Change the current identifiers into new ones defined in your metadata file. +Can be used for sample ID as well as variable ID. + + + +----------- +Input files +----------- + ++----------------------------+---------+ +| Parameter : num + label | Format | ++============================+=========+ +| 1 : Data matrix file | tabular | ++----------------------------+---------+ +| 2 : Metadata file | tabular | ++----------------------------+---------+ + + +Data matrix file contains the intensity values of the variables. + | + +Metadata file is meant to be chosen from sample metadata and variable metadata files. + | It should include a column containing your wanted IDs. + | + +---------- +Parameter +---------- + +Which ID do you want to change? + | This must be consistant with the metadata file you chose as input + | + +Name of the column to consider as new ID + | Must be one of your metadata file's column + | + +Force unicity if not unique? + | If no (default value), if your ID column does not contain unique values, it will stop the process and send you back an explicit error. + | If yes, non-unique values will be converted by adding "_x" at the end of concerned IDs. + | + + +------------ +Output file +------------ + +ID_metadata + | tabular output + | Corresponds to the input metadata file with new IDs as first column + | + +ID_datamatrix + | tabular output + | Corresponds to the input data matrix file with new IDs + | + + +--------------------------------------------------- + +---------------------- +Additional information +---------------------- + + +.. class:: warningmark + +For more information about input files, refer to the corresponding "W4M HowTo" page: + | `W4M table format for Galaxy <http://workflow4metabolomics.org/sites/workflow4metabolomics.org/files/files/w4m_TableFormatForGalaxy_150908.pdf>`_ + | + + + + + + \ No newline at end of file diff -r 000000000000 -r b7a6a88f518a IDchoice/IDchoice_script.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/IDchoice_script.R Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,124 @@ +################################################################################################ +# ID CHOICE # +# # +# User: Galaxy # +# Starting date: 01-06-2017 # +# V-0.1: First version of code # +# # +# # +# Input files: dataMatrix ; Metadata file # +# Output files: dataMatrix ; Metadata file # +# # +# Dependencies: RcheckLibrary.R ; miniTools.R (easyRlibrary) # +# # +################################################################################################ + +# Parameters (for dev) +if(FALSE){ + DM.name <- "CaracSpe_dataMatrix.txt" + meta.name <- "CaracSpe_variableMetadata.txt" + metype <- "variable" + #coloname <- "namecustom" + coloname <- "B" + makeun <- "yes" + DMout <- "ID_DM.txt" + metaout <- paste0("ID_",metype,"meta.txt") +} + + +id.choice <- function(DM.name,meta.name,metype,coloname,makeun,DMout,metaout){ + # This function allows to replace original IDs with other ones from one metadata table. + # + # Parameters: + # - DM.name, meta.name: dataMatrix and metadata files' access respectively + # - metype: "sample" or "variable" depending on metadata content + # - coloname: name of the metadata column to be used as new ID + # - makeun: "yes" or "no" depending on user choice if new IDs are not unique ("yes"=conversion to unique ID) + # - DMout, metaout: output files' access + + +# Input -------------------------------------------------------------- + +DM <- read.table(DM.name,header=TRUE,sep="\t",check.names=FALSE) +meta <- read.table(meta.name,header=TRUE,sep="\t",check.names=FALSE,colClasses="character") + +# Table match check +table.check <- match2(DM,meta,metype) +check.err(table.check) + + +# Checking unicity of new IDs ---------------------------------------- + +numcol <- which(colnames(meta)==coloname) +if(length(numcol)==0) { + stop(paste0("\n-------\nWarning: no '",coloname,"' column detected in ",metype," metadata!", + "\nPlease check your metadata file (column names are case-sensitive).\n-------\n")) +} + +unicity <- duplicated(meta[,numcol]) + +if(sum(unicity)>0){ + if(makeun=="no"){ + #Sending back an explicit error + duptable <- t(t(table(meta[,numcol][unicity])+1)) + stop(paste0("\n-------\nYour '",coloname,"' column contains duplicates:\n"), + paste(rownames(duptable),duptable,sep=": ",collapse="\n"),paste0("\nSince identifiers are meant to be unique, ", + "please check your data or use the 'Force unicity' option to force unicity.\n-------\n")) + + }else{ + #Making unique names + meta <- cbind(meta,newID=make.unique(meta[,numcol],sep="_"),ori=c(1:nrow(meta))) + } +}else{ + #No unicity problem + meta <- cbind(meta,newID=meta[,numcol],ori=c(1:nrow(meta))) +} + + +# Merging tables ----------------------------------------------------- + +#Transposing the dataMatrix if necessary +if(metype=="sample"){ + rownames(DM) <- DM[,1] + DM <- DM[,-1] + DM <- t(DM) + DM <- data.frame(sample=row.names(DM),DM,check.names=FALSE) + rownames(DM) <- NULL +} + +comb.data <- merge(x=meta,y=DM,by.x=1,by.y=1) +comb.data <- comb.data[order(comb.data$ori),] + + +# Changing IDs ------------------------------------------------------- + +DM <- comb.data[,-c(1:(ncol(meta)-2),ncol(meta))] +if(makeun=="no"){ + comb.data <- comb.data[,c(numcol,which(colnames(meta)!=coloname))] + meta <- comb.data[,c(1:(ncol(meta)-2))] +}else{ + meta <- comb.data[,c(ncol(meta)-1,1:(ncol(meta)-2))] +} + +#Transposing back the dataMatrix if necessary +if(metype=="sample"){ + rownames(DM) <- DM[,1] + DM <- DM[,-1] + DM <- t(DM) + DM <- data.frame(sample=row.names(DM),DM,check.names=FALSE) + rownames(DM) <- NULL +} + + +# Output ------------------------------------------------------------- + +# Writing the table +write.table(DM,DMout,sep="\t",quote=FALSE,row.names=FALSE) +write.table(meta,metaout,sep="\t",quote=FALSE,row.names=FALSE) + + +} # End of id.choice + + +# Typical function call +# id.choice(DM.name,meta.name,metype,coloname,makeun,DMout,metaout) diff -r 000000000000 -r b7a6a88f518a IDchoice/IDchoice_wrap.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/IDchoice_wrap.R Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,38 @@ +#!/usr/bin/Rscript --vanilla --slave --no-site-file + +################################################################################################ +# WRAPPER FOR IDchoice_script.R (ID CHOICE) # +# # +# Author: Melanie PETERA # +# User: Galaxy # +# Original data: used with IDchoice_script.R # +# Starting date: 01-06-2017 # +# V-1: Firt version of wrapper # +# # +# # +# Input files: dataMatrix ; Metadata file # +# Output files: dataMatrix ; Metadata file # +# # +################################################################################################ + + +library(batch) #necessary for parseCommandArgs function +args = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects + +source_local <- function(...){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + for(i in 1:length(list(...))){source(paste(base_dir, list(...)[[i]], sep="/"))} +} +#Import the different functions +source_local("IDchoice_script.R","easyrlibrary-lib/RcheckLibrary.R","easyrlibrary-lib/miniTools.R") + + +if(length(args) < 7){ stop("NOT enough argument !!!") } + + +id.choice(args$dataMatrix_in, args$Metadata_in, args$metatype, args$col_name, args$makeunique, args$DM_out, args$meta_out) + + +#delete the parameters to avoid the passage to the next tool in .RData image +rm(args) diff -r 000000000000 -r b7a6a88f518a IDchoice/README.md --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/README.md Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,60 @@ +ID choice +======= + +Metadata +----------- + + * **@name**: ID choice + * **@version**: 17.11 + * **@authors**: Melanie Petera - PFEM ; INRA ; MetaboHUB + * **@init date**: 2017/06/07 + * **@main usage**: This tool is designed to make you choose a particular column in your metadata file to be considered as identifiers for your W4M-3-tables-format data. + + +Context +----------- + +This tool is one of the [Workflow4Metabolomics](http://workflow4metabolomics.org) Galaxy instance utilities. W4M is a French infrastructure providing software tools to process, analyse and annotate metabolomics data. + +User interface is based on the Galaxy platform (homepage: https://galaxyproject.org/). It is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses. + + +Configuration +----------- + +### Requirement: + * R software: version > 3.0.0 recommended + * Specific R library: 'batch' + * Submodule: [easyRlibrary](https://github.com/workflow4metabolomics/easyrlibrary-lib) (Required for internal input quality checks) + +### Deploy: + * [get project data](https://github.com/workflow4metabolomics/idchoice) + * How to get the submodule files: +When pulling this module's Git repository, you may only obtain an empty folder for the needed submodule. +You can initialise it then with the following command: +```bash +git submodule update --init --recursive +``` + + +Travis test +----------- + +[![Build Status](https://travis-ci.org/workflow4metabolomics/idchoice.svg?branch=master)](https://travis-ci.org/workflow4metabolomics/idchoice) +Test and Deploy with Confidence. Easily sync your GitHub projects with Travis CI and you'll be testing your code in minutes! + + +Technical description +----------- + +Main files: + +- IDchoice_script.R: R function (core script) +- IDchoice_wrap.R: R script to link the main R function to inputs +- IDchoice.xml: XML wrapper (interface for Galaxy) + + +Services provided +----------- + + * Help and support: support@workflow4metabolomics.org diff -r 000000000000 -r b7a6a88f518a IDchoice/easyrlibrary-lib/RcheckLibrary.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/easyrlibrary-lib/RcheckLibrary.R Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,124 @@ +###################################################### +# R check library +# Coded by: M.Petera, +# - - +# R functions to use in R scripts +# (management of various generic subroutines) +# - - +# V0: script structure + first functions +# V1: More detailed error messages in match functions +###################################################### + + +# Generic function to return an error if problems have been encountered - - - - + +check.err <- function(err.stock){ + + # err.stock = vector of results returned by check functions + + if(length(err.stock)!=0){ stop("\n- - - - - - - - -\n",err.stock,"\n- - - - - - - - -\n") } + +} + + + + +# Table match check functions - - - - - - - - - - - - - - - - - - - - - - - - - + +# To check if dataMatrix and (variable or sample)Metadata match regarding identifiers +match2 <- function(dataMatrix, Metadata, Mtype){ + + # dataMatrix = data.frame containing dataMatrix + # Metadata = data.frame containing sampleMetadata or variableMetadata + # Mtype = "sample" or "variable" depending on Metadata content + + err.stock <- NULL # error vector + + id2 <- Metadata[,1] + if(Mtype=="sample"){ id1 <- colnames(dataMatrix)[-1] } + if(Mtype=="variable"){ id1 <- dataMatrix[,1] } + + if( length(which(id1%in%id2))!=length(id1) || length(which(id2%in%id1))!=length(id2) ){ + err.stock <- c("\nData matrix and ",Mtype," metadata do not match regarding ",Mtype," identifiers.") + if(length(which(id1%in%id2))!=length(id1)){ + if(length(which(!(id1%in%id2)))<4){ err.stock <- c(err.stock,"\n The ") + }else{ err.stock <- c(err.stock,"\n For example, the ") } + err.stock <- c(err.stock,"following identifiers found in the data matrix\n", + " do not appear in the ",Mtype," metadata file:\n") + identif <- id1[which(!(id1%in%id2))][1:min(3,length(which(!(id1%in%id2))))] + err.stock <- c(err.stock," ",paste(identif,collapse="\n "),"\n") + } + if(length(which(id2%in%id1))!=length(id2)){ + if(length(which(!(id2%in%id1)))<4){ err.stock <- c(err.stock,"\n The ") + }else{ err.stock <- c(err.stock,"\n For example, the ") } + err.stock <- c(err.stock,"following identifiers found in the ",Mtype," metadata file\n", + " do not appear in the data matrix:\n") + identif <- id2[which(!(id2%in%id1))][1:min(3,length(which(!(id2%in%id1))))] + err.stock <- c(err.stock," ",paste(identif,collapse="\n "),"\n") + } + err.stock <- c(err.stock,"\nPlease check your data.\n") + } + + return(err.stock) + +} + +# To check if the 3 standard tables match regarding identifiers +match3 <- function(dataMatrix, sampleMetadata, variableMetadata){ + + # dataMatrix = data.frame containing dataMatrix + # sampleMetadata = data.frame containing sampleMetadata + # variableMetadata = data.frame containing variableMetadata + + err.stock <- NULL # error vector + + id1 <- colnames(dataMatrix)[-1] + id2 <- sampleMetadata[,1] + id3 <- dataMatrix[,1] + id4 <- variableMetadata[,1] + + if( length(which(id1%in%id2))!=length(id1) || length(which(id2%in%id1))!=length(id2) ){ + err.stock <- c(err.stock,"\nData matrix and sample metadata do not match regarding sample identifiers.") + if(length(which(id1%in%id2))!=length(id1)){ + if(length(which(!(id1%in%id2)))<4){ err.stock <- c(err.stock,"\n The ") + }else{ err.stock <- c(err.stock,"\n For example, the ") } + err.stock <- c(err.stock,"following identifiers found in the data matrix\n", + " do not appear in the sample metadata file:\n") + identif <- id1[which(!(id1%in%id2))][1:min(3,length(which(!(id1%in%id2))))] + err.stock <- c(err.stock," ",paste(identif,collapse="\n "),"\n") + } + if(length(which(id2%in%id1))!=length(id2)){ + if(length(which(!(id2%in%id1)))<4){ err.stock <- c(err.stock,"\n The ") + }else{ err.stock <- c(err.stock,"\n For example, the ") } + err.stock <- c(err.stock,"following identifiers found in the sample metadata file\n", + " do not appear in the data matrix:\n") + identif <- id2[which(!(id2%in%id1))][1:min(3,length(which(!(id2%in%id1))))] + err.stock <- c(err.stock," ",paste(identif,collapse="\n "),"\n") + } + } + + if( length(which(id3%in%id4))!=length(id3) || length(which(id4%in%id3))!=length(id4) ){ + err.stock <- c(err.stock,"\nData matrix and variable metadata do not match regarding variable identifiers.") + if(length(which(id3%in%id4))!=length(id3)){ + if(length(which(!(id3%in%id4)))<4){ err.stock <- c(err.stock,"\n The ") + }else{ err.stock <- c(err.stock,"\n For example, the ") } + err.stock <- c(err.stock,"following identifiers found in the data matrix\n", + " do not appear in the variable metadata file:\n") + identif <- id3[which(!(id3%in%id4))][1:min(3,length(which(!(id3%in%id4))))] + err.stock <- c(err.stock," ",paste(identif,collapse="\n "),"\n") + } + if(length(which(id4%in%id3))!=length(id4)){ + if(length(which(!(id4%in%id3)))<4){ err.stock <- c(err.stock,"\n The ") + }else{ err.stock <- c(err.stock,"\n For example, the ") } + err.stock <- c(err.stock,"following identifiers found in the variable metadata file\n", + " do not appear in the data matrix:\n") + identif <- id4[which(!(id4%in%id3))][1:min(3,length(which(!(id4%in%id3))))] + err.stock <- c(err.stock," ",paste(identif,collapse="\n "),"\n") + } + } + + if(length(err.stock)!=0){ err.stock <- c(err.stock,"\nPlease check your data.\n") } + + return(err.stock) + +} \ No newline at end of file diff -r 000000000000 -r b7a6a88f518a IDchoice/easyrlibrary-lib/miniTools.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/easyrlibrary-lib/miniTools.R Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,133 @@ +##################################################### +# Mini tools for Galaxy scripting +# Coded by: M.Petera, +# - - +# R functions to use in R scripts and wrappers +# to make things easier (lightening code, reducing verbose...) +# - - +# V0: script structure + first functions +# V1: addition of functions to handle special characters in identifiers +##################################################### + + +# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +# Function to call packages without printing all the verbose +# (only getting the essentials, like warning messages for example) + +shyLib <- function(...){ + for(i in 1:length(list(...))){ + suppressPackageStartupMessages(library(list(...)[[i]],character.only=TRUE)) + } +} + +#example: shyLib("xcms","pcaMethods") + + + +# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +# Fonction pour sourcer les scripts R requis +# /!\ ATTENTION : actuellement la fonction n'est pas chargee au lancement du script, +# il faut donc la copier-coller dans le wrapper R pour pouvoir l'utiliser. + +if(FALSE){ +source_local <- function(...){ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + for(i in 1:length(list(...))){ + source(paste(base_dir, list(...)[[i]], sep="/")) + } +} +} + +#example: source_local("filter_script.R","RcheckLibrary.R") + + + +# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +# Functions to stock identifiers before applying make.names() and +# to reinject it into final matrices +# Note: it reproduces the original order of datasets' identifiers +# - - - +# stockID: stocks original identifiers and original order +# -> needs checked data regarding table match +# reproduceID: reinjects original identifiers and original order into final tables +# -> function to be used at the very end, when exporting tables + +stockID <- function(dataMatrix, Metadata, Mtype){ + # dataMatrix = data.frame containing dataMatrix + # Metadata = data.frame containing sampleMetadata or variableMetadata + # Mtype = "sample" or "variable" depending on Metadata content + cname <- colnames(dataMatrix)[1] + # dataMatrix temporary-stock + transfo - - - - + if(Mtype=="sample"){ + id.ori <- colnames(dataMatrix)[-1] + colnames(dataMatrix) <- make.names(colnames(dataMatrix)) + } + if(Mtype=="variable"){ + id.ori <- dataMatrix[,1] + dataMatrix[,1] <- make.names(dataMatrix[,1]) + } + # global stock - - - - - - - - - - - - - - - - + id.new <- data.frame(order.ori=c(1:length(Metadata[,1])),Metadata[,1], + id.new=make.names(Metadata[,1]),id.ori, + id.new.DM=make.names(id.ori),stringsAsFactors=FALSE) + colnames(id.new)[c(2,4)] <- c(colnames(Metadata)[1],cname) + # Metadata transfo + returning data - - - - - + Metadata[,1] <- make.names(Metadata[,1]) + return(list(id.match=id.new, dataMatrix=dataMatrix, Metadata=Metadata)) +} +#example: A<-stockID(myDM,mysM,"sample") ; myDM<-A$dataMatrix ; mysM<-A$Metadata ; A<-A$id.match + +reproduceID <- function(dataMatrix, Metadata, Mtype, id.match){ + # dataMatrix = data.frame containing dataMatrix + # Metadata = data.frame containing sampleMetadata or variableMetadata + # Mtype = "sample" or "variable" depending on Metadata content + # id.match = 'id.match' element produced by stockID + #Metadada - - - - - - - - - - - - - - + temp.table <- id.match[,c(1,2,3)] + ## Removing deleted rows + for(i in 1:(dim(id.match)[1])){ + if(!(temp.table[i,3]%in%Metadata[,1])){temp.table[i,1] <- 0} + } + if(length(which(temp.table[,1]==0))!=0){ + temp.table <- temp.table[-c(which(temp.table[,1]==0)),] + } + ## Restoring original identifiers and order + temp.table <- merge(x=temp.table,y=Metadata,by.x=3,by.y=1) + temp.table <- temp.table[order(temp.table$order.ori),] + Metadata <- temp.table[,-c(1,2)] + rownames(Metadata) <- NULL + #dataMatrix - - - - - - - - - - - - - + rownames(dataMatrix)<-dataMatrix[,1] + if(Mtype=="sample"){ + dataMatrix <- t(dataMatrix[,-1]) + } + temp.table <- id.match[,c(1,4,5)] + ## Removing deleted rows + for(i in 1:(dim(id.match)[1])){ + if(!(temp.table[i,3]%in%rownames(dataMatrix))){temp.table[i,1] <- 0} + } + if(length(which(temp.table[,1]==0))!=0){ + temp.table <- temp.table[-c(which(temp.table[,1]==0)),] + } + ## Restoring original identifiers and order + temp.table <- merge(x=temp.table,y=dataMatrix,by.x=3,by.y=0) + temp.table <- temp.table[order(temp.table$order.ori),] + if(Mtype=="variable"){ + dataMatrix <- temp.table[,-c(1,2,4)] + colnames(dataMatrix)[1] <- colnames(id.match)[4] + } else { + rownames(temp.table) <- temp.table[,3] + temp.table <- t(temp.table[,-c(1,2,3)]) + dataMatrix <- data.frame(rownames(temp.table),temp.table) + colnames(dataMatrix)[1] <- colnames(id.match)[4] + } + rownames(dataMatrix) <- NULL + # return datasets - - - - - - - - - - - + return(list(dataMatrix=dataMatrix, Metadata=Metadata)) +} +#example: B<-reproduceID(myDM,mysM,"sample",A) ; myDM<-B$dataMatrix ; mysM<-B$Metadata + + + +# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff -r 000000000000 -r b7a6a88f518a IDchoice/planemo_test.sh --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/planemo_test.sh Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,3 @@ +planemo conda_init --conda_prefix /tmp/mc/ +planemo conda_install --conda_prefix /tmp/mc/ . +planemo test --install_galaxy --conda_dependency_resolution --conda_prefix /tmp/mc/ --no_cleanup \ No newline at end of file diff -r 000000000000 -r b7a6a88f518a IDchoice/test-data/input_IDc_dataMatrix.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/test-data/input_IDc_dataMatrix.txt Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,18 @@ +data j 785 y54j 68y4j6 5-6 4 hrh 5h - 3 t564 t54 66 y6y t6 5h (5y g51 ( 6 98 j7-0 06654h 60 +5d_-kkcùf 0.356426723610756 0.380152310071702 0.0306944207412024 0.334137638848017 0.298147485608469 0.975073793297568 0.129099504745855 0.973451663994064 0.334792719284834 0.0751565260418877 0.322897933010729 0.129033714279026 0.722966330196726 0.580654367692078 0.644502528016206 0.352827235332827 0.511778286438001 +npèt 0.801750949101246 0.535593104115636 0.258351312473067 0.599475573145688 0.0763319665667417 0.504558103160623 0.367963830290116 0.440540211857668 0.158066366765388 0.609574253877002 0.550590276177951 0.232864384033621 0.637065775537391 0.424098276140436 0.662053737304139 0.0217541227637467 0.299053946391647 +5PY4(*3 0.875199970420953 0.0825428101366147 0.253659010703906 0.507762246807195 0.856444177031262 0.291594962324086 0.616538655402613 0.388475672176377 0.914254939740854 0.449607330807756 0.628469388494906 0.436558212905713 0.951198610265672 0.956459387015831 0.0113483457928278 0.611559621193868 0.127393349941781 +k 0.235214515530521 0.50917637648828 0.0303152651414629 0.305595242012361 0.470145996588881 0.356776179776951 0.569840649303474 0.720070419680388 0.875026990189028 0.97246313990283 0.936423978578332 0.810603455355391 0.903046784946495 0.667091730522105 0.0282601148338295 0.276666638740528 0.747503427028951 +t v^ptok!R/; 0.251801918471682 0.871383805557867 0.285183681272061 0.552739436194454 0.863766301215097 0.182656918760194 0.977603710051043 0.204845724382198 0.751690583305025 0.751475804910098 0.938399878874186 0.218163132174348 0.523463794277572 0.987156468237196 0.630938391969655 0.495061607430081 0.815474132321848 +ojt* 0.907412839750932 0.857498273276021 0.370137361785406 0.76678484779183 0.213299689296413 0.521214352529346 0.0851731095099456 0.868227767553325 0.0711706993343434 0.70186429888193 0.700568035764899 0.7467824290166 0.570332959002042 0.23270290523468 0.126423339798572 0.816262268500797 0.466363859676536 +lmtki 0.344288940919619 0.308219131305663 0.218449898667526 0.700869668247368 0.932538878977527 0.396198994630489 0.710306820874376 0.124235068279782 0.56608643523601 0.887647287670482 0.0375011938139768 0.282378766400105 0.757492159558571 0.506567258021703 0.990910788272054 0.326205008250378 0.61003856679129 +1h6-(587 t 0.308709890328272 0.717202505490233 0.777934118812417 0.604807545422864 0.588458968776734 0.940112596977594 0.788662314418432 0.133046934771924 0.891405172730758 0.915119678712577 0.401136527896346 0.996068607925829 0.049077648050296 0.157657286859101 0.598183619914656 0.439531332356748 0.11995300831499 +r154 (54 86 0.0861033910635205 0.243889357950567 0.848801588667359 0.972183114768299 0.311829870889657 0.434854970574638 0.0240613698880671 0.273335646139236 0.902686361056168 0.73479376111027 0.232132726965829 0.471097756642369 0.511949019774828 0.934158039531663 0.60125450357768 0.972297241140637 0.63149263296722 +(h4 0.336373953934809 0.521412085356266 0.281632887739949 0.67004516763179 0.0199332367594847 0.867732114278491 0.973477443505332 0.883197938525362 0.334509105447652 0.793947578560618 0.465167375556954 0.508757674191867 0.983758014396725 0.100582744588671 0.501301982240787 0.789637338939369 0.967382850752139 +2 0.65083934802851 0.915695024588 0.0376667088550816 0.514003854683931 0.274761574286474 0.652108809243866 0.689393057486628 0.262205073769319 0.871958663956254 0.709490850507154 0.854477673591409 0.672918329289054 0.141693817710263 0.00543057257281332 0.273084303937691 0.39570748778882 0.303196826092465 + m(yk 0.798331012769621 0.806128809071498 0.519974578571807 0.0237856823099186 0.396426673475168 0.75979784245693 0.0589336105092753 0.763144123705766 0.16086904822931 0.301000258395631 0.321186481311644 0.0091434029302796 0.0346149352313591 0.276366137673702 0.686099471259438 0.0548240244354505 0.909361338008149 + -546 -3 -3 0.981561422839383 0.755973696318293 0.328878596436459 0.233341270249666 0.14569201922932 0.458105216271765 0.191023237667199 0.775603857680909 0.146769440956804 0.86812372109824 0.601678275863019 0.782019307745586 0.955614654474782 0.836058192741214 0.454550085076576 0.181788519803465 0.325277631599655 +nz^à t 0.920089977342539 0.249031996586174 0.105577675363886 0.805216649434891 0.505774902707566 0.619612431793644 0.337662179244335 0.672829320507873 0.387228581340173 0.209795853201976 0.0403285073621635 0.540614252108851 0.43362855410287 0.160204078494507 0.924783730297701 0.116837628312753 0.58763473928668 +kzjù 0.418651623550921 0.668434005412235 0.845525871017258 0.567468950919516 0.111441846749533 0.411424602517146 0.0743349602270699 0.583730221710347 0.0105008018078939 0.918789674284249 0.808643595994088 0.33578972219198 0.536848200622412 0.898842910125025 0.333954421105444 0.0390509357521919 0.159857705429294 +. Glk(ôepjg$ 0.3266193089274 0.806668730531573 0.87265879590923 0.934940869880726 0.548967615908753 0.250539517744596 0.75436043048449 0.597444122305604 0.343955002787363 0.560987092777944 0.134929631392942 0.958047956861493 0.870429681664852 0.66286672214456 0.441523248613101 0.437073092741238 0.265031623006715 +rmlgj*lr , 0.462672931523031 0.74679446664976 0.151929368261195 0.165870989887449 0.90931621240424 0.423706631494886 0.337742032589001 0.184993498717115 0.0792523932129463 0.071353352835237 0.525247607449536 0.647744088759121 0.158725526449032 0.203927461340644 0.20055683200405 0.897053444943847 0.506954538974894 diff -r 000000000000 -r b7a6a88f518a IDchoice/test-data/input_IDc_sampleMetadata.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/test-data/input_IDc_sampleMetadata.txt Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,18 @@ +data ABCD E AAA fp uv +j 785 1 91 a a s +y54j 68y4j6 2 60 b z d +5-6 4 2 43 c e f +hrh 3 24 d r s +5h - 4 29 b t d +3 56 71 a y f +t564 4 4 r u s +t54 66 23 91 c i d +y6y 5 61 f o f +t6 5h 8 21 s p s +(5y 98 77 b q d +g51 67 1 b s f +( 98 48 r d s +6 2 10 a f d +98 j7-0 1 36 a g f +06654h 34 100 k h s +60 67 38 d j d diff -r 000000000000 -r b7a6a88f518a IDchoice/test-data/input_IDc_variableMetadata.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/test-data/input_IDc_variableMetadata.txt Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,18 @@ +variable A B C D +5d_-kkcùf 0 a ze$ùj 0 +npèt 1 b g 0 +5PY4(*3 2 c 15j-è, 0 +k 3 a 6jè 1 +t v^ptok!R/; 4 b 8j4, 1 +ojt* 5 c 5èj1 1 +lmtki 6 a j84 2 +1h6-(587 t 7 b j4e54 2 +r154 (54 86 8 c j 2 +(h4 9 a 54j6@44èu6(è4 3 +2 10 b (51h 3 + m(yk 11 c 8-1 3 + -546 -3 -3 12 a hy-81u 4 +nz^à t 13 b zs5-hj1 4 +kzjù 14 c 861h 4 +. Glk(ôepjg$ 15 a (8168(h1 9 +rmlgj*lr , 16 b 8hjè1 9 diff -r 000000000000 -r b7a6a88f518a IDchoice/test-data/output1_IDc_dataMatrix.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/test-data/output1_IDc_dataMatrix.tabular Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,18 @@ +newID j 785 y54j 68y4j6 5-6 4 hrh 5h - 3 t564 t54 66 y6y t6 5h (5y g51 ( 6 98 j7-0 06654h 60 +a 0.356426723610756 0.380152310071702 0.0306944207412024 0.334137638848017 0.298147485608469 0.975073793297568 0.129099504745855 0.973451663994064 0.334792719284834 0.0751565260418877 0.322897933010729 0.129033714279026 0.722966330196726 0.580654367692078 0.644502528016206 0.352827235332827 0.511778286438001 +b 0.801750949101246 0.535593104115636 0.258351312473067 0.599475573145688 0.0763319665667417 0.504558103160623 0.367963830290116 0.440540211857668 0.158066366765388 0.609574253877002 0.550590276177951 0.232864384033621 0.637065775537391 0.424098276140436 0.662053737304139 0.0217541227637467 0.299053946391647 +c 0.875199970420953 0.0825428101366147 0.253659010703906 0.507762246807195 0.856444177031262 0.291594962324086 0.616538655402613 0.388475672176377 0.914254939740854 0.449607330807756 0.628469388494906 0.436558212905713 0.951198610265672 0.956459387015831 0.0113483457928278 0.611559621193868 0.127393349941781 +a_1 0.235214515530521 0.50917637648828 0.0303152651414629 0.305595242012361 0.470145996588881 0.356776179776951 0.569840649303474 0.720070419680388 0.875026990189028 0.97246313990283 0.936423978578332 0.810603455355391 0.903046784946495 0.667091730522105 0.0282601148338295 0.276666638740528 0.747503427028951 +b_1 0.251801918471682 0.871383805557867 0.285183681272061 0.552739436194454 0.863766301215097 0.182656918760194 0.977603710051043 0.204845724382198 0.751690583305025 0.751475804910098 0.938399878874186 0.218163132174348 0.523463794277572 0.987156468237196 0.630938391969655 0.495061607430081 0.815474132321848 +c_1 0.907412839750932 0.857498273276021 0.370137361785406 0.76678484779183 0.213299689296413 0.521214352529346 0.0851731095099456 0.868227767553325 0.0711706993343434 0.70186429888193 0.700568035764899 0.7467824290166 0.570332959002042 0.23270290523468 0.126423339798572 0.816262268500797 0.466363859676536 +a_2 0.344288940919619 0.308219131305663 0.218449898667526 0.700869668247368 0.932538878977527 0.396198994630489 0.710306820874376 0.124235068279782 0.56608643523601 0.887647287670482 0.0375011938139768 0.282378766400105 0.757492159558571 0.506567258021703 0.990910788272054 0.326205008250378 0.61003856679129 +b_2 0.308709890328272 0.717202505490233 0.777934118812417 0.604807545422864 0.588458968776734 0.940112596977594 0.788662314418432 0.133046934771924 0.891405172730758 0.915119678712577 0.401136527896346 0.996068607925829 0.049077648050296 0.157657286859101 0.598183619914656 0.439531332356748 0.11995300831499 +c_2 0.0861033910635205 0.243889357950567 0.848801588667359 0.972183114768299 0.311829870889657 0.434854970574638 0.0240613698880671 0.273335646139236 0.902686361056168 0.73479376111027 0.232132726965829 0.471097756642369 0.511949019774828 0.934158039531663 0.60125450357768 0.972297241140637 0.63149263296722 +a_3 0.336373953934809 0.521412085356266 0.281632887739949 0.67004516763179 0.0199332367594847 0.867732114278491 0.973477443505332 0.883197938525362 0.334509105447652 0.793947578560618 0.465167375556954 0.508757674191867 0.983758014396725 0.100582744588671 0.501301982240787 0.789637338939369 0.967382850752139 +b_3 0.65083934802851 0.915695024588 0.0376667088550816 0.514003854683931 0.274761574286474 0.652108809243866 0.689393057486628 0.262205073769319 0.871958663956254 0.709490850507154 0.854477673591409 0.672918329289054 0.141693817710263 0.00543057257281332 0.273084303937691 0.39570748778882 0.303196826092465 +c_3 0.798331012769621 0.806128809071498 0.519974578571807 0.0237856823099186 0.396426673475168 0.75979784245693 0.0589336105092753 0.763144123705766 0.16086904822931 0.301000258395631 0.321186481311644 0.0091434029302796 0.0346149352313591 0.276366137673702 0.686099471259438 0.0548240244354505 0.909361338008149 +a_4 0.981561422839383 0.755973696318293 0.328878596436459 0.233341270249666 0.14569201922932 0.458105216271765 0.191023237667199 0.775603857680909 0.146769440956804 0.86812372109824 0.601678275863019 0.782019307745586 0.955614654474782 0.836058192741214 0.454550085076576 0.181788519803465 0.325277631599655 +b_4 0.920089977342539 0.249031996586174 0.105577675363886 0.805216649434891 0.505774902707566 0.619612431793644 0.337662179244335 0.672829320507873 0.387228581340173 0.209795853201976 0.0403285073621635 0.540614252108851 0.43362855410287 0.160204078494507 0.924783730297701 0.116837628312753 0.58763473928668 +c_4 0.418651623550921 0.668434005412235 0.845525871017258 0.567468950919516 0.111441846749533 0.411424602517146 0.0743349602270699 0.583730221710347 0.0105008018078939 0.918789674284249 0.808643595994088 0.33578972219198 0.536848200622412 0.898842910125025 0.333954421105444 0.0390509357521919 0.159857705429294 +a_5 0.3266193089274 0.806668730531573 0.87265879590923 0.934940869880726 0.548967615908753 0.250539517744596 0.75436043048449 0.597444122305604 0.343955002787363 0.560987092777944 0.134929631392942 0.958047956861493 0.870429681664852 0.66286672214456 0.441523248613101 0.437073092741238 0.265031623006715 +b_5 0.462672931523031 0.74679446664976 0.151929368261195 0.165870989887449 0.90931621240424 0.423706631494886 0.337742032589001 0.184993498717115 0.0792523932129463 0.071353352835237 0.525247607449536 0.647744088759121 0.158725526449032 0.203927461340644 0.20055683200405 0.897053444943847 0.506954538974894 diff -r 000000000000 -r b7a6a88f518a IDchoice/test-data/output1_IDc_variableMetadata.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/test-data/output1_IDc_variableMetadata.tabular Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,18 @@ +newID variable A B C D +a 5d_-kkcùf 0 a ze$ùj 0 +b npèt 1 b g 0 +c 5PY4(*3 2 c 15j-è, 0 +a_1 k 3 a 6jè 1 +b_1 t v^ptok!R/; 4 b 8j4, 1 +c_1 ojt* 5 c 5èj1 1 +a_2 lmtki 6 a j84 2 +b_2 1h6-(587 t 7 b j4e54 2 +c_2 r154 (54 86 8 c j 2 +a_3 (h4 9 a 54j6@44èu6(è4 3 +b_3 2 10 b (51h 3 +c_3 m(yk 11 c 8-1 3 +a_4 -546 -3 -3 12 a hy-81u 4 +b_4 nz^à t 13 b zs5-hj1 4 +c_4 kzjù 14 c 861h 4 +a_5 . Glk(ôepjg$ 15 a (8168(h1 9 +b_5 rmlgj*lr , 16 b 8hjè1 9 diff -r 000000000000 -r b7a6a88f518a IDchoice/test-data/output2_IDc_dataMatrix.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/test-data/output2_IDc_dataMatrix.tabular Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,18 @@ +sample a b c d b_1 a_1 r c_1 f s b_2 b_3 r_1 a_2 a_3 k d_1 +5d_-kkcùf 0.356426723610756 0.380152310071702 0.0306944207412024 0.334137638848017 0.298147485608469 0.975073793297568 0.129099504745855 0.973451663994064 0.334792719284834 0.0751565260418877 0.322897933010729 0.129033714279026 0.722966330196726 0.580654367692078 0.644502528016206 0.352827235332827 0.511778286438001 +npèt 0.801750949101246 0.535593104115636 0.258351312473067 0.599475573145688 0.0763319665667417 0.504558103160623 0.367963830290116 0.440540211857668 0.158066366765388 0.609574253877002 0.550590276177951 0.232864384033621 0.637065775537391 0.424098276140436 0.662053737304139 0.0217541227637467 0.299053946391647 +5PY4(*3 0.875199970420953 0.0825428101366147 0.253659010703906 0.507762246807195 0.856444177031262 0.291594962324086 0.616538655402613 0.388475672176377 0.914254939740854 0.449607330807756 0.628469388494906 0.436558212905713 0.951198610265672 0.956459387015831 0.0113483457928278 0.611559621193868 0.127393349941781 +k 0.235214515530521 0.50917637648828 0.0303152651414629 0.305595242012361 0.470145996588881 0.356776179776951 0.569840649303474 0.720070419680388 0.875026990189028 0.97246313990283 0.936423978578332 0.810603455355391 0.903046784946495 0.667091730522105 0.0282601148338295 0.276666638740528 0.747503427028951 +t v^ptok!R/; 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Glk(ôepjg$ 0.3266193089274 0.806668730531573 0.87265879590923 0.934940869880726 0.548967615908753 0.250539517744596 0.75436043048449 0.597444122305604 0.343955002787363 0.560987092777944 0.134929631392942 0.958047956861493 0.870429681664852 0.66286672214456 0.441523248613101 0.437073092741238 0.265031623006715 +rmlgj*lr , 0.462672931523031 0.74679446664976 0.151929368261195 0.165870989887449 0.90931621240424 0.423706631494886 0.337742032589001 0.184993498717115 0.0792523932129463 0.071353352835237 0.525247607449536 0.647744088759121 0.158725526449032 0.203927461340644 0.20055683200405 0.897053444943847 0.506954538974894 diff -r 000000000000 -r b7a6a88f518a IDchoice/test-data/output2_IDc_sampleMetadata.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/IDchoice/test-data/output2_IDc_sampleMetadata.tabular Thu Oct 11 05:47:29 2018 -0400 @@ -0,0 +1,18 @@ +newID data ABCD E AAA fp uv +a j 785 1 91 a a s +b y54j 68y4j6 2 60 b z d +c 5-6 4 2 43 c e f +d hrh 3 24 d r s +b_1 5h - 4 29 b t d +a_1 3 56 71 a y f +r t564 4 4 r u s +c_1 t54 66 23 91 c i d +f y6y 5 61 f o f +s t6 5h 8 21 s p s +b_2 (5y 98 77 b q d +b_3 g51 67 1 b s f +r_1 ( 98 48 r d s +a_2 6 2 10 a f d +a_3 98 j7-0 1 36 a g f +k 06654h 34 100 k h s +d_1 60 67 38 d j d