# HG changeset patch
# User workflow4metabolomics
# Date 1611074507 0
# Node ID 58997c28b268574be068715760ce3d4c62467ec1

"planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics/blob/master/tools/correlation_analysis/ commit 35a01e4ef59a91f43d0b1de1d08db29dcc7aae1e"

diff -r 000000000000 -r 58997c28b268 abims_correlation_analysis.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/abims_correlation_analysis.xml	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,322 @@
+<tool id="correlation_analysis" name="Metabolites Correlation Analysis" version="1.0.1+galaxy0" >
+
+    <description>to highlight ion correlations considering PC-groups</description>
+
+    <requirements>
+        <requirement type="package" version="1.1_5">r-batch</requirement>
+        <requirement type="package" version="0.8.8">r-reshape</requirement>
+        <requirement type="package" version="7.3_53">r-mass</requirement>
+    </requirements>
+
+    <command detect_errors='exit_code'>
+        Rscript '$__tool_directory__/correlation_analysis.r'
+
+        #if $cond_input_type.select_input_type == "select_input_from_w4m" and $cond_input_type.cond_function.select_funtion == "sort_only" :
+            sorting 1 variable_metadata '$cond_input_type.variableMetadata'
+            data_matrix '$cond_input_type.dataMatrix'
+            sample_metadata '$cond_input_type.sampleMetadata'
+            corrdel 0
+            param_correlation ""
+            param_cytoscape ""
+            matrix_corr 0
+            user_matrix_corr ""
+            corr_method ""
+        #end if
+        #if $cond_input_type.select_input_type == "select_input_from_w4m" and $cond_input_type.cond_function.select_funtion == "sort_and_corr" :
+            sorting 1
+            variable_metadata '$cond_input_type.variableMetadata'
+            data_matrix '$cond_input_type.dataMatrix'
+            sample_metadata '$cond_input_type.sampleMetadata'
+            corrdel 1
+            param_correlation $cond_input_type.cond_function.param_correlation
+            param_cytoscape $cond_input_type.cond_function.param_cytoscape
+            matrix_corr 0
+            user_matrix_corr ""
+            corr_method $cond_input_type.cond_function.corr_method
+        #end if
+        ##Create correlation matrix from a user table file.##
+        #if $cond_input_type.select_input_type == "select_input_other" :
+            sorting 0
+            variable_metadata ""
+            data_matrix ""
+            sample_metadata ""
+            corrdel 0
+            param_correlation ""
+            param_cytoscape $cond_input_type.param_cytoscape
+            matrix_corr 1
+            user_matrix_corr '$cond_input_type.user_matrix_corr'
+            corr_method $cond_input_type.corr_method
+        #end if
+
+    </command>
+
+    <inputs>
+
+
+         <conditional name="cond_input_type" >
+            <param name="select_input_type" type="select" label="Choice of your input files" help="" >
+                <option value="select_input_from_w4m" selected="true">Files from the metabolomic workflow</option>
+                <option value="select_input_other" >Your table file</option>
+            </param>
+            <when value="select_input_from_w4m">
+                <param name="dataMatrix" type="data" label="Data matrix" format="tabular" help="dataMatrix file from the CAMERA.annotate step for example" />
+                <param name="sampleMetadata" type="data" label="Sample metadata" format="tabular" help="sampleMetadata file from the xcms.xcmsSet step for example" />
+                <param name="variableMetadata" type="data" label="Variable metadata" format="tabular" help="variableMetadata file from the CAMERA.annotate step for example" />
+                <conditional name="cond_function" >
+                    <param name="select_funtion" type="select" label="Function to be used" help="" >
+                        <option value="sort_only" selected="true">Sorting your table</option>
+                        <option value="sort_and_corr" >Sorting your table and doing correlation analysis</option>
+                    </param>
+                    <when value="sort_only" />
+                    <when value="sort_and_corr">
+                         <param name="corrdel" type="hidden" value="1"/>
+                         <param name="param_correlation" type="float" label="Correlation threshold for pcgroup" value="0.60" help="Threshold value for selecting edges (i.e. correlations) that will be exported to the Cytoscape sif format file" />
+                         <param name="corr_method" type="select" label="Choice of the correlation method" help="" >
+                            <option value="pearson" selected="true">pearson</option>
+                            <option value="kendall">kendall</option>
+                            <option value="spearman">spearman</option>
+                         </param>
+                         <param name="param_cytoscape" type="float" label="Cytoscape correlation threshold" value="0.75" help="Choose a threshold value for selecting metabolites that will be exported to a cytoscape sif format" />
+                    </when>
+                </conditional>
+            </when>
+
+            <when value="select_input_other">
+                <param name="user_matrix_corr" type="data" label="Your table file (tabular format)" format="tabular" help="Your metabolites (variables) intensity table file (tabular format)" />
+                <param name="corr_method" type="select" label="Choice of the correlation method" help="" >
+                    <option value="pearson" selected="true">pearson</option>
+                    <option value="kendall">kendall</option>
+                    <option value="spearman">spearman</option>
+                </param>
+                <param name="param_cytoscape" type="float" label="Cytoscape correlation threshold" value="0.75" help="Threshold value for selecting edges (i.e. correlations) that will be exported to the Cytoscape sif format file" />
+            </when>
+        </conditional>
+    </inputs>
+
+    <outputs>
+        <data name="sorted_table" format="tabular" from_work_dir="sorted_table.tsv" label="sorted_variableMetadata.tsv">
+             <filter>(cond_input_type['select_input_type'] == 'select_input_from_w4m')</filter>
+        </data>
+        <data name="correlation_matrix_selected" format="tabular" from_work_dir="correlation_matrix_selected.tsv" label="correlation_matrix_selected.tsv">
+            <filter>(cond_input_type['select_input_type'] == 'select_input_from_w4m' and cond_input_type['cond_function']['select_funtion']== 'sort_and_corr' and cond_input_type['cond_function']['corrdel']== '1' )</filter>
+        </data>
+        <data name="siff_table" format="tabular" from_work_dir="siff_table.tsv" label="sif_table.tsv">
+            <filter>(cond_input_type['select_input_type'] == 'select_input_from_w4m' and cond_input_type['cond_function']['select_funtion']== 'sort_and_corr' and cond_input_type['cond_function']['corrdel']== '1' )</filter>
+        </data>
+        <data name="correlation_matrix_user" format="tabular" from_work_dir="correlation_matrix.tsv" label="correlation_matrix.tsv">
+            <filter>(cond_input_type['select_input_type'] == 'select_input_other')</filter>
+        </data>
+        <data name="siff_table_user_user" format="tabular" from_work_dir="siff_table.tsv" label="sif_table.tsv">
+            <filter>(cond_input_type['select_input_type'] == 'select_input_other')</filter>
+        </data>
+    </outputs>
+
+    <tests>
+        <test expect_num_outputs="3">
+            <conditional name="cond_input_type" >
+                <param name="select_input_type" value="select_input_from_w4m" />
+                <param name="dataMatrix" value="in_DM1.tabular" ftype="tabular" />
+                <param name="sampleMetadata" value="in_SM1.tabular" ftype="tabular" />
+                <param name="variableMetadata" value="in_VM1.tabular" ftype="tabular" />
+                <conditional name="cond_function" >
+                    <param name="select_funtion" value="sort_and_corr" />
+                </conditional>
+            </conditional>
+            <output name="sorted_table" file="out_VM1.tabular"/>
+            <output name="correlation_matrix_selected" file="out_corr1.tabular"/>
+            <output name="siff_table" file="out_sif1.tabular"/>
+        </test>
+    </tests>
+
+    <help>
+
+.. class:: infomark
+
+**Authors** Antoine Gravot (Protocole conception) and Misharl Monsoor (for initial galaxy wrapper and R script).
+
+**Additional W4M contributors** ABiMS TEAM (SU/CNRS - Station biologique de Roscoff) and PFEM (INRAE - MetaboHUB)
+
+---------------------------------------------------
+
+================================
+Metabolites correlation analysis
+================================
+
+-----------
+Description
+-----------
+
+This tool takes as inputs either tabular table files from the metabolomic workflow (variableMetadata, dataMatrix and sampleMetadata) or a table file of your own
+and can execute three different functions ("sorting", "corrdel" and "corr_matrix").
+
+**The "sorting" function:** *used for metabolomic workflow*
+
+ | 1) First of all, it sorts the data by pcgroup.
+ | 2) It computes the mean operation of all the signal values of the metabolites by sample, and put the results in a new column "signal_moy".
+ | 3) It finally creates a tabular output "sorted_variableMetadata.tsv".
+
+**The "corrdel" function:** *used for metabolomic workflow*
+
+ | **For each pcgroup** of the previous sorted tabular file "sorted_table.tsv", it does the following things:
+ | - it computes a correlation matrix
+ | - it determines the metabolites which are not correlated to others from the same pcgroup based on the threshold value filled in the "Correlation threshold for pcgroup" parameter
+ | - the metabolites are sorted by the mean signal intensity (form the highest to the lowest), and each metabolite is tested to the previous ones in the list ; if the tested metabolite is at least correlated to one previous one, it is tagged as DEL (for "deleted", written in a column called "suppress")
+ |
+ | It creates two additional tabular files:
+ | - "correlation_matrix_selected.tsv" (correlation matrix of selected metabolites only)
+ | - "sif_table.tsv" (for visualization in CytoScape, based on selected metabolites and "Cytoscape correlation threshold" filled value)
+
+
+**The "corr_matrix" function:** *used for user table file*
+
+ | It computes a correlation matrix named "correlation_matrix.tsv" and creates a sif file named "sif_table.tsv" (for visualization in CytoScape).
+
+
+
+-----------------
+Workflow position
+-----------------
+
+
+**Examples of upstream tools**
+
++---------------------------+--------------------------+--------+------------------------+
+| Name                      | Output file              | Format | parameter              |
++===========================+==========================+========+========================+
+|xcms findChromPeaks Merger |sampleMetada.tsv          | Tabular| Sample metadata        |
++---------------------------+--------------------------+--------+------------------------+
+|xcms fillChromPeaks        |dataMatrix.tsv            | Tabular| Data matrix            |
++---------------------------+--------------------------+--------+------------------------+
+|CAMERA.annotate            |variableMetadata.tsv      | Tabular| Variable metadata      |
++---------------------------+--------------------------+--------+------------------------+
+
+
+
+**Examples of downstream tools**
+
++---------------------------+--------------------------------------+--------+
+| Name                      | Output file                          | Format |
++===========================+======================================+========+
+|Hierarchical Clustering    |selected_metabolites_transpo.tsv      | Tabular|
++---------------------------+--------------------------------------+--------+
+|ANOVA                      |selected_metabolites_transpo.tsv      | Tabular|
++---------------------------+--------------------------------------+--------+
+
+
+
+**General schema of the metabolomic workflow**
+
+.. image:: MetaboAnalysisCorrelation_workflow.png
+
+-----------
+Input files
+-----------
+
++--------------------------------+------------+
+| Parameter: label               | Format     |
++================================+============+
+| Data matrix                    | Tabular    |
++--------------------------------+------------+
+| Sample metadata                | Tabular    |
++--------------------------------+------------+
+| Variable metadata              | Tabular    |
++--------------------------------+------------+
+| User table file                | Tabular    |
++--------------------------------+------------+
+
+
+----------
+Parameters
+----------
+
+**Choice of your input files**
+
+ | **variableMetadata**
+ |
+ | For example, the "variableMetadata.tsv" tabular file generated by the CAMERA.annotate step of the workflow.
+ | This table must contain in particular two columns named "**pcgroup**" and "**rt**" (it is case-sensitive).
+ |
+ | **dataMatrix**
+ |
+ | For example, the "dataMatrix.tsv" tabular file generated by the CAMERA.annotate step of the workflow.
+ |
+ | **sampleMetadata**
+ |
+ | For example, the tabular file with the samples metadata generated by the xcmsSet step: one sample per line and at least two columns: ids and one variable.
+ |
+ | **user table**
+ |
+ | Tabular containing intensities where your variables (metabolites) are in columns (for example a transposition of your datamatrix file)
+
+**Correlation threshold for pcgroup** *(metabolomic workflow only)*
+
+The threshold value that will determine if two metabolites are correlated inside a same pcgroup after the creation of the global correlation matrix.
+If you do not want to use the intra-pcgroup filter (see "corrdel" function in the description section), put this threshold to 1 and all ions will be kept.
+
+**Choice of the correlation method**
+
+Choose the correlation method (pearson, kendall or spearman).
+
+**Cytoscape correlation threshold**
+
+Choose a threshold value for selecting edges (i.e. correlations between metabolites) that will be exported to the Cytoscape sif format file.
+
+------------
+Output files
+------------
+
+
+
+**sorted_variableMetadata.tsv** *(metabolomic workflow only)*
+
+ | A tabular file which:
+ | 1) contains the original variable metadata columns
+ | 2) is sorted by the pcgroup column
+ | 3) contains a new column "signal_moy" (mean of all the signal values of the metabolites by sample)
+ | 4) (depending of parameters) contains a "suppress" column
+
+**correlation_matrix_selected.tsv** *(metabolomic workflow only)*
+
+ | A correlation matrix containing only the metabolites selected in each pcgroup (metabolites tagged as "DEL" in "suppress" column are removed),
+ | completed with two columns "rtmed" and "signal_moy".
+
+**sif_table.tsv**
+
+ | A tabular file (three columns: Metabolite1, Correlation coefficient, Metabolite 2) that can be used in Cytoscape.
+
+------
+
+.. class:: infomark
+
+The output **selected_metabolites_dataMatrix.tsv** is a tabular file. You can continue your analysis using it for example in the following statistical tools:
+ | Hierarchical Clustering
+ | ANOVA
+
+
+---------------------------------------------------
+
+Changelog/News
+--------------
+
+
+**Version 1.0.1+galaxy0 - 10/12/2020**
+
+- Update of some of the outputs' formats to match standard W4M table format
+- Standard output (stdout) log improvement
+- Change of testing data for faster job running for tests
+- Fix: generation of the outputs for "Your table file" option
+
+**Version 1.0.1 - 20/09/2016**
+
+- TEST: refactoring to pass functional test using conda dependencies
+- Help improvement
+
+
+**Version 20141118 - 18/11/2014**
+
+    </help>
+    <citations>
+        <citation type="doi">10.1093/bioinformatics/btu813</citation>
+    </citations>
+
+</tool>
diff -r 000000000000 -r 58997c28b268 correlation_analysis.r
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/correlation_analysis.r	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,213 @@
+#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file
+#For questions: Antoine Gravot (Protocole conception) and Misharl Monsoor  (for galaxy wrapper and R script).
+
+#Load the different libraries
+library(batch) #necessary for parseCommandArgs function
+library(reshape) #necessary for using melt function
+library(MASS) # necessary for using the write.matrix()
+#interpretation of arguments given in command line as an R list of objects
+list_arguments <- parseCommandArgs(evaluate = FALSE)
+
+cat("\nJob starting time:\n", format(Sys.time(), "%a %d %b %Y %X"),
+    "\n\n--------------------------------------------------------------------",
+    "\nParameters used in 'Metabolites Correlation Analysis':\n\n")
+print(list_arguments)
+cat("--------------------------------------------------------------------\n\n")
+
+#The main function of this script that will execute all the other functions
+
+
+main_function <- function(sorting, variable_metadata, data_matrix, sample_metadata, corrdel, param_correlation, param_cytoscape, matrix_corr, user_matrix_corr, corr_method) {
+
+
+    if (sorting == 1) {
+        ####Executing the sorting function####
+        cat("\nExecuting the sorting function\n")
+        #Read the tsv annotateDiffreport file and don't modify the columns name (check.names = FALSE)
+        variable_metadata_input <- read.csv(variable_metadata, header = T, sep = "\t", dec = ".", check.names = FALSE)
+        data_matrix_input <- read.csv(data_matrix, header = T, sep = "\t", dec = ".", check.names = FALSE)
+        first_column_variable <- toString(names(variable_metadata_input)[1])
+        first_column_datamatrix <- toString(names(data_matrix_input)[1])
+        #@TODO merge
+        input_tsv <- cbind(variable_metadata_input, data_matrix_input[, !(colnames(data_matrix_input) %in% c(first_column_datamatrix))])
+        #Load the sample.info from the xcmsSet
+        sample_metadata_info_tsv <- read.table(sample_metadata, header = T, sep = "\t", dec = ",", check.names = FALSE)
+        #Extract the samples name from the sample.info file generated from the xcmsSet step in ABIMS Workflow4Metabo.
+        samples_name <- as.vector(t(sample_metadata_info_tsv[1]))
+        output_tsv <- sorting(input_tsv, samples_name)
+        # output now if corrdel == 0
+        if (corrdel == 0) {
+          output_tsv_vm <- output_tsv[, which(!(colnames(output_tsv) %in% samples_name))]
+          write.table(output_tsv_vm[, c(3:ncol(output_tsv_vm), 2, 1)], sep = "\t", quote = FALSE, col.names = TRUE, row.names = FALSE, file = "sorted_table.tsv")
+        }
+
+    }
+    if (corrdel == 1) {
+        cat("\nExecuting the corr_matrix_del function\n")
+        corr_matrix_del(output_tsv, samples_name, param_correlation, param_cytoscape, corr_method)
+    }
+
+    if (matrix_corr == 1) {
+        cat("\nExecuting the corr_matrix function\n")
+        corr_matrix_user(user_matrix_corr, param_cytoscape, corr_method)
+
+    }
+
+}
+
+#The sorting function will sort the dataframe by rt column.
+#Then it creates a "signal_moy" column which contains the mean values of the signal values of the sample by row.
+#It finally creates a table tsv format "sorted_table.tsv".
+
+sorting <- function(input_tsv, samples_name) {
+
+    #Sort by rt column
+    new_input <- input_tsv[order(input_tsv$rt), ]
+    #Compute the mean operation of all the signal values of the sample by row, and put the results in a new column "signal_moy"
+    new_input["signal_moy"] <- data.frame(Means = rowMeans(new_input[, colnames(new_input) %in% samples_name]))
+    #Rearrange the data frame in order to have the columns "signal_moy" and "pcgroup" at the beginning of the table
+    new_input <- cbind(new_input["signal_moy"], new_input["pcgroup"], new_input[, !(colnames(new_input) %in% c("signal_moy", "pcgroup"))])
+    #Sort the "signal_moy" column data frame by pcgroup
+    new_input <- new_input[order(new_input$pcgroup, -new_input$signal_moy), ]
+    #Write the data frame to a file named "sorted_table.tsv"
+    #Erase the rownames of the table
+    rownames(new_input) <- NULL
+    #Suppress rows which contains Nas
+    new_input <- new_input[complete.cases(new_input$pcgroup), ]
+    return(new_input)
+}
+
+corr_matrix_del <- function(output_tsv, samples_name, param_correlation, param_cytoscape, corr_method) {
+
+    #statmatrix, a dataframe which contains only the columns "name" and the values of the intensity for all the samples
+    first_column <- toString(names(output_tsv)[3])
+    statmatrix <- output_tsv[(names(output_tsv) %in% c(first_column, samples_name))]
+    statmatrix2 <- output_tsv[(names(output_tsv) %in% c(first_column, "signal_moy", samples_name))]
+    n <- statmatrix[, first_column]
+    #transpose all but the first column (name)
+    statmatrix <- as.data.frame(t(statmatrix[, -1]))
+    #Rename the columns of the dataframe "statmatrix"
+    colnames(statmatrix) <- n
+    #Transform dataframe to matrix before doing the cor function
+    corr_transpo <- data.matrix(statmatrix)
+    #Create a matrix which contains only the data of the samples without the other columns
+    statmatrix <- output_tsv[(names(output_tsv) %in% c(samples_name))]
+    #Add the rownames previously
+    rownames(statmatrix) <- make.unique(as.vector(output_tsv[, first_column]))
+    #Do the cor step, with the transposed statmatrix (metabolites as columns)
+    corr_transpo <- cor(t(as.matrix(statmatrix)), method = corr_method)
+    #Add the columns "signal_moy", "pcgroup" and "name" to the final correlation matrix output
+    new_dataframe <- cbind(output_tsv["signal_moy"], output_tsv["pcgroup"], output_tsv[names(output_tsv)[3]], corr_transpo)
+    #Add a new column "suppress" which indicates if the metabolite will be removed from the analysis (because it is correlated with the other metabolite)
+    new_dataframe["suppress"] <- ""
+    #Take the pcgroup names
+    pcgroups <- unique(new_dataframe$pcgroup)
+    #Remove NAs from the pcgroups vector
+    pcgroups <- pcgroups[which(pcgroups != "NA")]
+    #Creates a pcgroups list
+    list_data <- vector(mode = "list", length = length(pcgroups))
+    #Will do the following steps by pcgroup
+    for (pcgroup in pcgroups) {
+        #Select a subset data frame for each pcgroup
+        subset_data <- new_dataframe[new_dataframe$pcgroup == pcgroup, ]
+        #Stores the metabolites names for each pcgroup into a matrix one dimension.
+        pc_group_elements <- t(as.matrix(subset_data[3]))
+        #uses the matrix "pc_group_elements" containing the metabolites to have the correlation data frame "subset_data2" by pcgroup
+        subset_data2 <- subset_data[names(subset_data) %in% c(names(output_tsv)[3], pc_group_elements)]
+        #We keep the first metabolites for each pcgroup that correspond to the metabolites with the highest amount of signal
+        first_metabolite <- pc_group_elements[1]
+        #Remove the first metabolite from the pc_group_elements matrix
+        pc_group_elements <- pc_group_elements[, c(seq_len(length(pc_group_elements)))]
+        #print (pc_group_elements)
+        for (metabolite in pc_group_elements) {
+            metabolite_dataframe <- subset_data2[subset_data2[, first_column] == metabolite, ]
+            #retrives metabolite index from the vector object "pc_group_elements"
+            index_metabolite <- as.numeric(which(pc_group_elements == metabolite, arr.ind = TRUE))
+            for (f in 2:index_metabolite - 1) {
+                if (metabolite != first_metabolite) {
+                    value_intensity <- t(data.matrix(metabolite_dataframe[, pc_group_elements[f]]))
+                    value_intensity <- value_intensity[1:1]
+                    #If one value is >0.75, it means that the metabolite est correlated with at least one previous metabolite in the table, so the boolean variable is set to true.
+                    if (value_intensity > param_correlation) {
+                        new_dataframe$suppress[new_dataframe[, first_column] == metabolite] <- "DEL"
+                    }
+                }
+            }
+        }
+    }
+    #The dataframe with the column "suppress" at the begginning
+    new_dataframe_suppression <- cbind(new_dataframe[first_column], new_dataframe["suppress"], output_tsv["rt"], new_dataframe["signal_moy"], new_dataframe[, !(colnames(new_dataframe) %in% c(first_column, "suppress", "pcgroup", "signal_moy"))])
+
+
+    #remove all the rows which have the "suppress" data and keep only the selected metabolites
+    selected_metabolite_dataframe <- new_dataframe_suppression[new_dataframe_suppression$suppress != "DEL", ]
+    #Keep the metabolites selected in a list
+    metabolites_selected_list <- as.vector(t(selected_metabolite_dataframe[1]))
+    #Add the other columns to keep
+    metabolites_selected_list <- c(metabolites_selected_list, first_column, "rt", "signal_moy")
+    #Keep the metabolites selected to keep only the columns
+    selected_metabolite_dataframe <- selected_metabolite_dataframe[, colnames(selected_metabolite_dataframe) %in% metabolites_selected_list]
+
+    #Export to siff table format for visualization in cytoscape for the selected metabolites
+    siff_table <- melt(selected_metabolite_dataframe[, !colnames(selected_metabolite_dataframe) %in% c("pcgroup", "rt", "signal_moy")])
+    #Remove the values equal to 1 (correlation between two metabolite identical)
+    siff_table <- siff_table[siff_table$value != 1, ]
+    #Keep only the values corresponding to the param_cytoscape
+    siff_table <- siff_table[siff_table$value >= param_cytoscape, ]
+    #Change the order of the columns
+    siff_table <- cbind(siff_table[first_column], siff_table["value"], siff_table["variable"])
+
+
+
+    #Join the two datasets to keep only the selected metabolite, with all the information about the intensity value for statistics analysis in the next step of the workflow.
+    joined_dataframe <- merge(statmatrix2, selected_metabolite_dataframe[first_column], by = first_column)
+    #Order by the signal intensity
+    joined_dataframe <- joined_dataframe[order(-joined_dataframe$signal_moy), ]
+    #Transposition of the dataframe
+    joined_dataframe <- joined_dataframe[, !(colnames(joined_dataframe) %in% c("signal_moy"))]
+
+
+    #Write the different tables into files
+    write.table(selected_metabolite_dataframe, sep = "\t", quote = FALSE, col.names = TRUE, row.names = FALSE, file = "correlation_matrix_selected.tsv")
+    write.table(siff_table, sep = "\t", quote = FALSE, col.names = FALSE, row.names = FALSE, file = "siff_table.tsv")
+    output_tsv_vm <- output_tsv[, which(!(colnames(output_tsv) %in% samples_name))]
+    output_tsv_vm <- data.frame(output_tsv_vm[, c(3:ncol(output_tsv_vm), 2, 1)], ori.or = seq_len(nrow(output_tsv_vm)))
+    output_tsv_vm <- merge(x = output_tsv_vm, y = new_dataframe[, c(3, which(colnames(new_dataframe) == "suppress"))], by.x = 1, by.y = 1, sort = FALSE)
+    output_tsv_vm <- output_tsv_vm[order(output_tsv_vm$ori.or), ][, -c(which(colnames(output_tsv_vm) == "ori.or"))]
+    write.table(output_tsv_vm, sep = "\t", quote = FALSE, col.names = TRUE, row.names = FALSE, file = "sorted_table.tsv")
+
+}
+
+
+corr_matrix_user <- function(user_matrix_corr, param_cytoscape, corr_method) {
+    #read the input table
+    input_tsv <- read.csv(user_matrix_corr, header = T, sep = "\t", dec = ".", check.names = FALSE)
+    n <- input_tsv$HD
+    #transpose all but the first column (name)
+    statmatrix_corr <- as.data.frame(t(input_tsv[, -1]))
+    #Rename the columns of the dataframe "statmatrix"
+    colnames(statmatrix_corr) <- n
+    #Do the cor step, with the transposed statmatrix.
+    corr_transpo <- cor(t(as.matrix(statmatrix_corr)), method = corr_method)
+    #Write the matrix to a tsv file
+    write.table(corr_transpo, sep <- "\t", quote = FALSE, col.names = NA, file = "correlation_matrix.tsv")
+    #Export to siff table format for visualization in cytoscape for the selected conditions
+    siff_table <- melt(corr_transpo)
+    #Remove the values equal to 1 (correlation between two metabolite identical)
+    siff_table <- siff_table[siff_table$value != 1, ]
+    #Keep only the values corresponding to the param_cytoscape
+    siff_table <- siff_table[siff_table$value >= param_cytoscape, ]
+    #Change the order of the columns
+    siff_table <- cbind(Node1 = siff_table["X1"], interaction = siff_table["value"], Node2 = siff_table["X2"])
+    #Write the siff table
+    write.table(siff_table, sep = "\t", quote = FALSE, col.names = FALSE, row.names = FALSE, file = "siff_table.tsv")
+
+}
+do.call(main_function, list_arguments)
+
+
+cat("\n--------------------------------------------------------------------",
+    "\nInformation about R (version, Operating System, attached or loaded packages):\n\n")
+sessionInfo()
+cat("--------------------------------------------------------------------\n",
+    "\nJob ending time:\n", format(Sys.time(), "%a %d %b %Y %X"))
diff -r 000000000000 -r 58997c28b268 static/images/MetaboAnalysisCorrelation_workflow.png
Binary file static/images/MetaboAnalysisCorrelation_workflow.png has changed
diff -r 000000000000 -r 58997c28b268 test-data/in_DM1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/in_DM1.tabular	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,746 @@
+ions	Sample1	Sample2	Sample3	Sample4	Sample5	Sample6	Sample7	Sample8	Sample9	Sample10	Sample11	Sample12	Sample13	Sample14	Sample15	Sample16	Sample17	Sample18	Sample19	Sample20	Sample21	Sample22	Sample23	Sample24	Sample25	Sample26	Sample27	Sample28	Sample29	Sample30	Sample31	Sample32	Sample33	Sample34	Sample35	Sample36	Sample37	Sample38	Sample39	Sample40	Sample41	Sample42	Sample43	Sample44	Sample45	Sample46	Sample47	Sample48	Sample49
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diff -r 000000000000 -r 58997c28b268 test-data/in_SM1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/in_SM1.tabular	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,50 @@
+sampleMetadata	batch	injectionOrder	sampleType	Time	Group
+Sample1	s1	2	sample	1	A
+Sample2	s1	3	sample	2	B
+Sample3	s1	17	sample	4	C
+Sample4	s1	20	sample	3	B
+Sample5	s1	47	sample	1	A
+Sample6	s1	48	sample	2	B
+Sample7	s2	59	sample	4	A
+Sample8	s2	64	sample	2	C
+Sample9	s2	86	sample	4	C
+Sample10	s2	87	sample	1	A
+Sample11	s2	96	sample	3	B
+Sample12	s2	97	sample	1	C
+Sample13	s3	105	sample	2	B
+Sample14	s3	106	sample	4	A
+Sample15	s3	107	sample	3	D
+Sample16	s3	113	sample	1	A
+Sample17	s3	114	sample	2	C
+Sample18	s3	120	sample	1	B
+Sample19	s3	126	sample	4	A
+Sample20	s4	155	sample	2	B
+Sample21	s4	158	sample	1	C
+Sample22	s4	159	sample	3	A
+Sample23	s4	171	sample	4	B
+Sample24	s4	172	sample	2	A
+Sample25	s4	173	sample	1	C
+Sample26	s4	177	sample	4	F
+Sample27	s4	178	sample	1	F
+Sample28	s4	181	sample	2	F
+Sample29	s4	182	sample	3	F
+Sample30	s2	52	pool	5	E
+Sample31	s2	63	pool	5	E
+Sample32	s2	83	pool	5	E
+Sample33	s2	93	pool	5	E
+Sample34	s2	102	pool	5	E
+Sample35	s3	103	pool	5	E
+Sample36	s3	112	pool	5	E
+Sample37	s3	132	pool	5	E
+Sample38	s3	143	pool	5	E
+Sample39	s3	152	pool	5	E
+Sample40	s4	163	pool	5	E
+Sample41	s4	174	pool	5	E
+Sample42	s4	185	pool	5	E
+Sample43	s4	196	pool	5	E
+Sample44	s1	1	pool	5	E
+Sample45	s1	11	pool	5	E
+Sample46	s1	22	pool	5	E
+Sample47	s1	28	pool	5	E
+Sample48	s1	39	pool	5	E
+Sample49	s1	51	pool	5	E
diff -r 000000000000 -r 58997c28b268 test-data/in_VM1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/in_VM1.tabular	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,746 @@
+ions	mz	rt	mode	pcgroup
+p100.023T0.7	100.023	0.7	pos	32
+p102.97T0.7	102.97	0.7	pos	32
+p104.106T1	104.106	1	pos	21
+p104.107T12.1	104.107	12.1	pos	52
+p104.107T12.7	104.107	12.7	pos	56
+p105.033T6	105.033	6	pos	22
+p106.951T0.8	106.951	0.8	pos	33
+p107.072T15.4	107.072	15.4	pos	74
+p116.068T1.1	116.068	1.1	pos	35
+p119.047T1.5	119.047	1.5	pos	39
+p119.047T4.2	119.047	4.2	pos	102
+p120.077T4.5	120.077	4.5	pos	104
+p120.079T6.5	120.079	6.5	pos	119
+p121.081T4.5	121.081	4.5	pos	104
+p121.082T6.5	121.082	6.5	pos	119
+p123.042T4.2	123.042	4.2	pos	102
+p128.016T0.7	128.016	0.7	pos	32
+p130.048T0.9	130.048	0.9	pos	34
+p131.046T4.5	131.046	4.5	pos	104
+p131.069T8.7	131.069	8.7	pos	137
+p132.073T1.2	132.073	1.2	pos	36
+p132.086T5.3	132.086	5.3	pos	109
+p133.087T15.4	133.087	15.4	pos	74
+p133.087T8.7	133.087	8.7	pos	137
+p135.023T12.7	135.023	12.7	pos	56
+p136.072T4.2	136.072	4.2	pos	102
+p137.042T1.3	137.042	1.3	pos	37
+p137.048T4.2	137.048	4.2	pos	102
+p144.077T5.3	144.077	5.3	pos	109
+p146.095T8.7	146.095	8.7	pos	137
+p147.061T5.3	147.061	5.3	pos	109
+p148.06T1.3	148.06	1.3	pos	37
+p149.022T17.3	149.022	17.3	pos	90
+p149.02T13.7	149.02	13.7	pos	62
+p149.057T4.5	149.057	4.5	pos	104
+p150.01T0.9	150.01	0.9	pos	34
+p150.057T1.3	150.057	1.3	pos	37
+p151.033T0.7	151.033	0.7	pos	32
+p152.067T4.5	152.067	4.5	pos	104
+p158.965T0.8	158.965	0.8	pos	33
+p165.052T4.2	165.052	4.2	pos	102
+p166.084T4.5	166.084	4.5	pos	104
+p166.085T7.2	166.085	7.2	pos	125
+p166.086T6.5	166.086	6.5	pos	119
+p167.036T17.3	167.036	17.3	pos	90
+p167.086T4.5	167.086	4.5	pos	104
+p169.033T1.3	169.033	1.3	pos	37
+p170.032T1.3	170.032	1.3	pos	37
+p170.058T5.3	170.058	5.3	pos	109
+p174.94T0.8	174.94	0.8	pos	33
+p174.991T10.9	174.991	10.9	pos	45
+p175.116T0.9	175.116	0.9	pos	34
+p177.053T0.8	177.053	0.8	pos	33
+p177.115T15.4	177.115	15.4	pos	74
+p179.07T6.9	179.07	6.9	pos	123
+p179.143T13.1	179.143	13.1	pos	58
+p182.073T5.2	182.073	5.2	pos	108
+p182.08T1.4	182.08	1.4	pos	38
+p182.08T4.2	182.08	4.2	pos	102
+p182.09T9.3	182.09	9.3	pos	141
+p184.073T12.4	184.073	12.4	pos	54
+p185.027T1.3	185.027	1.3	pos	37
+p188.027T6.1	188.027	6.1	pos	115
+p189.022T6.1	189.022	6.1	pos	115
+p189.073T5.3	189.073	5.3	pos	109
+p189.086T1.2	189.086	1.2	pos	36
+p189.098T16.2	189.098	16.2	pos	80
+p192.136T4.7	192.136	4.7	pos	106
+p194.098T9.8	194.098	9.8	pos	144
+p194.117T4.3	194.117	4.3	pos	103
+p195.088T5.7	195.088	5.7	pos	112
+p196.09T5.7	196.09	5.7	pos	112
+p196.129T15.4	196.129	15.4	pos	74
+p196.87T0.9	196.87	0.9	pos	34
+p198.941T0.7	198.941	0.7	pos	32
+p200.034T0.9	200.034	0.9	pos	34
+p203.054T0.9	203.054	0.9	pos	34
+p204.057T0.9	204.057	0.9	pos	34
+p205.159T13.6	205.159	13.6	pos	61
+p207.024T0.9	207.024	0.9	pos	34
+p207.053T6.1	207.053	6.1	pos	115
+p209.118T10.7	209.118	10.7	pos	44
+p213.233T8.7	213.233	8.7	pos	137
+p214.916T0.7	214.916	0.7	pos	32
+p216.925T0.9	216.925	0.9	pos	34
+p217.106T4.6	217.106	4.6	pos	105
+p219.082T0.9	219.082	0.9	pos	34
+p219.992T13.7	219.992	13.7	pos	62
+p220.936T0.8	220.936	0.8	pos	33
+p221.14T8.7	221.14	8.7	pos	137
+p226.952T0.8	226.952	0.8	pos	33
+p228.957T0.8	228.957	0.8	pos	33
+p230.891T0.7	230.891	0.7	pos	32
+p239.064T1.2	239.064	1.2	pos	36
+p239.09T7.1	239.09	7.1	pos	124
+p239.151T15.4	239.151	15.4	pos	74
+p240.101T12.4	240.101	12.4	pos	54
+p240.155T15.4	240.155	15.4	pos	74
+p240.233T9.7	240.233	9.7	pos	143
+p242.928T0.8	242.928	0.8	pos	33
+p247.139T1.3	247.139	1.3	pos	37
+p251.048T14.8	251.048	14.8	pos	69
+p254.976T1.1	254.976	1.1	pos	35
+p255.16T10.2	255.16	10.2	pos	40
+p256.265T15.3	256.265	15.3	pos	73
+p257.267T15.3	257.267	15.3	pos	73
+p269.232T15.5	269.232	15.5	pos	75
+p270.235T15.5	270.235	15.5	pos	75
+p270.28T15.7	270.28	15.7	pos	76
+p271.129T6.1	271.129	6.1	pos	115
+p271.264T15.4	271.264	15.4	pos	74
+p271.274T16.1	271.274	16.1	pos	79
+p272.259T10.3	272.259	10.3	pos	41
+p272.943T0.8	272.943	0.8	pos	33
+p276.055T13.7	276.055	13.7	pos	62
+p276.12T1.2	276.12	1.2	pos	36
+p276.145T4.2	276.145	4.2	pos	102
+p279.17T6.3	279.17	6.3	pos	117
+p283.178T15.4	283.178	15.4	pos	74
+p285.268T16.1	285.268	16.1	pos	79
+p285.294T16.7	285.294	16.7	pos	85
+p286.127T1.3	286.127	1.3	pos	37
+p286.144T10.9	286.144	10.9	pos	45
+p286.202T7.3	286.202	7.3	pos	126
+p286.223T15.3	286.223	15.3	pos	73
+p288.133T12.1	288.133	12.1	pos	52
+p288.217T8	288.217	8	pos	24
+p288.923T0.8	288.923	0.8	pos	33
+p299.106T5.1	299.106	5.1	pos	107
+p300.289T14.7	300.289	14.7	pos	68
+p302.085T5.4	302.085	5.4	pos	110
+p302.135T13.7	302.135	13.7	pos	62
+p303.233T13.3	303.233	13.3	pos	60
+p304.238T13.3	304.238	13.3	pos	60
+p305.304T11.3	305.304	11.3	pos	48
+p310.13T4.6	310.13	4.6	pos	105
+p310.917T0.8	310.917	0.8	pos	33
+p313.034T0.8	313.034	0.8	pos	33
+p313.155T6.5	313.155	6.5	pos	119
+p314.031T12.7	314.031	12.7	pos	56
+p314.16T6.5	314.16	6.5	pos	119
+p315.291T15.4	315.291	15.4	pos	74
+p317.253T9.1	317.253	9.1	pos	139
+p326.126T1.3	326.126	1.3	pos	37
+p326.149T4.2	326.149	4.2	pos	102
+p326.167T15	326.167	15	pos	29
+p326.379T12.6	326.379	12.6	pos	55
+p327.05T0.8	327.05	0.8	pos	33
+p327.079T12.6	327.079	12.6	pos	55
+p327.207T15.3	327.207	15.3	pos	73
+p327.383T12.6	327.383	12.6	pos	55
+p328.083T12.6	328.083	12.6	pos	55
+p328.249T9.1	328.249	9.1	pos	139
+p328.285T15.5	328.285	15.5	pos	75
+p328.316T16.1	328.316	16.1	pos	79
+p329.24T17.4	329.24	17.4	pos	91
+p332.332T12.2	332.332	12.2	pos	53
+p334.303T15.4	334.303	15.4	pos	74
+p338.344T15.4	338.344	15.4	pos	74
+p339.168T15.5	339.168	15.5	pos	75
+p339.189T16.3	339.189	16.3	pos	81
+p340.18T6.5	340.18	6.5	pos	119
+p341.216T16.3	341.216	16.3	pos	81
+p341.268T14.7	341.268	14.7	pos	68
+p342.264T9.6	342.264	9.6	pos	142
+p344.258T13.3	344.258	13.3	pos	60
+p344.28T10.2	344.28	10.2	pos	40
+p347.31T16.1	347.31	16.1	pos	79
+p353.265T15.5	353.265	15.5	pos	75
+p353.296T16.4	353.296	16.4	pos	82
+p355.077T16.2	355.077	16.2	pos	80
+p356.074T15.8	356.074	15.8	pos	77
+p356.121T16.2	356.121	16.2	pos	80
+p356.226T16.1	356.226	16.1	pos	79
+p356.288T15.4	356.288	15.4	pos	74
+p357.278T11.7	357.278	11.7	pos	50
+p357.289T15.4	357.289	15.4	pos	74
+p358.296T10.5	358.296	10.5	pos	42
+p361.333T16.7	361.333	16.7	pos	85
+p362.196T6.6	362.196	6.6	pos	120
+p363.931T0.8	363.931	0.8	pos	33
+p364.326T14.6	364.326	14.6	pos	67
+p366.373T20	366.373	20	pos	31
+p367.319T17.8	367.319	17.8	pos	94
+p369.226T15	369.226	15	pos	29
+p369.299T16.1	369.299	16.1	pos	79
+p370.301T16.1	370.301	16.1	pos	79
+p371.258T15.4	371.258	15.4	pos	74
+p371.286T16.1	371.286	16.1	pos	79
+p372.233T5.6	372.233	5.6	pos	111
+p372.31T11.1	372.31	11.1	pos	46
+p378.903T0.8	378.903	0.8	pos	33
+p379.341T15.4	379.341	15.4	pos	74
+p380.219T16.3	380.219	16.3	pos	81
+p380.256T11	380.256	11	pos	26
+p384.32T16.7	384.32	16.7	pos	85
+p385.292T14.6	385.292	14.6	pos	67
+p388.253T5.7	388.253	5.7	pos	112
+p390.984T1.3	390.984	1.3	pos	37
+p391.344T16.1	391.344	16.1	pos	79
+p393.209T5.7	393.209	5.7	pos	112
+p393.363T16.1	393.363	16.1	pos	79
+p399.308T15.4	399.308	15.4	pos	74
+p400.314T15.4	400.314	15.4	pos	74
+p400.342T12.1	400.342	12.1	pos	52
+p401.316T15.4	401.316	15.4	pos	74
+p402.32T15.4	402.32	15.4	pos	74
+p405.359T16.7	405.359	16.7	pos	85
+p406.375T16.7	406.375	16.7	pos	85
+p407.335T14.6	407.335	14.6	pos	67
+p407.337T16.3	407.337	16.3	pos	81
+p407.381T16.7	407.381	16.7	pos	85
+p408.318T16.1	408.318	16.1	pos	79
+p409.292T6.6	409.292	6.6	pos	120
+p413.269T17.3	413.269	17.3	pos	90
+p413.325T16.1	413.325	16.1	pos	79
+p414.273T17.3	414.273	17.3	pos	90
+p414.328T16.1	414.328	16.1	pos	79
+p414.3T10.3	414.3	10.3	pos	41
+p415.252T5.8	415.252	5.8	pos	113
+p416.257T5.8	416.257	5.8	pos	113
+p418.193T6.5	418.193	6.5	pos	119
+p418.194T4.3	418.194	4.3	pos	103
+p423.383T15.4	423.383	15.4	pos	74
+p424.342T11.7	424.342	11.7	pos	50
+p424.386T15.4	424.386	15.4	pos	74
+p424.897T0.8	424.897	0.8	pos	33
+p427.337T16.7	427.337	16.7	pos	85
+p427.358T16.1	427.358	16.1	pos	79
+p428.346T16.7	428.346	16.7	pos	85
+p429.354T16.7	429.354	16.7	pos	85
+p430.302T7.4	430.302	7.4	pos	127
+p430.323T14.6	430.323	14.6	pos	67
+p430.913T0.8	430.913	0.8	pos	33
+p432.311T10.3	432.311	10.3	pos	41
+p433.241T7.2	433.241	7.2	pos	125
+p433.24T7.8	433.24	7.8	pos	130
+p433.284T5.8	433.284	5.8	pos	113
+p435.368T16.1	435.368	16.1	pos	79
+p436.283T12.4	436.283	12.4	pos	54
+p436.394T16.1	436.394	16.1	pos	79
+p437.235T5.8	437.235	5.8	pos	113
+p437.393T16.1	437.393	16.1	pos	79
+p438.299T12.8	438.299	12.8	pos	57
+p439.381T15.4	439.381	15.4	pos	74
+p443.333T15.4	443.333	15.4	pos	74
+p444.341T15.4	444.341	15.4	pos	74
+p445.314T6.2	445.314	6.2	pos	116
+p445.344T15.4	445.344	15.4	pos	74
+p446.889T0.8	446.889	0.8	pos	33
+p449.386T16.7	449.386	16.7	pos	85
+p450.413T16.7	450.413	16.7	pos	85
+p454.294T12.4	454.294	12.4	pos	54
+p455.285T7.2	455.285	7.2	pos	125
+p455.333T16.3	455.333	16.3	pos	81
+p455.363T18.4	455.363	18.4	pos	97
+p458.354T16.1	458.354	16.1	pos	79
+p458.783T7	458.783	7	pos	23
+p459.279T6	459.279	6	pos	22
+p459.311T15.4	459.311	15.4	pos	74
+p459.358T16.1	459.358	16.1	pos	79
+p464.237T10.6	464.237	10.6	pos	43
+p464.314T13.2	464.314	13.2	pos	59
+p464.314T14	464.314	14	pos	28
+p465.329T16.2	465.329	16.2	pos	80
+p466.332T14.5	466.332	14.5	pos	66
+p466.334T16.3	466.334	16.3	pos	81
+p467.412T15.4	467.412	15.4	pos	74
+p468.308T11.2	468.308	11.2	pos	47
+p469.312T11.2	469.312	11.2	pos	47
+p470.309T16.7	470.309	16.7	pos	85
+p470.316T11.2	470.316	11.2	pos	47
+p472.311T7.2	472.311	7.2	pos	125
+p472.311T7.9	472.311	7.9	pos	131
+p472.372T16.7	472.372	16.7	pos	85
+p473.345T14.6	473.345	14.6	pos	67
+p476.304T6	476.304	6	pos	22
+p477.267T7.2	477.267	7.2	pos	125
+p477.267T7.9	477.267	7.9	pos	131
+p477.309T6	477.309	6	pos	22
+p478.297T11.9	478.297	11.9	pos	51
+p479.298T11.9	479.298	11.9	pos	51
+p479.39T16.1	479.39	16.1	pos	79
+p481.399T16.1	481.399	16.1	pos	79
+p482.324T12	482.324	12	pos	27
+p482.325T14	482.325	14	pos	28
+p482.359T13.3	482.359	13.3	pos	60
+p483.328T12	483.328	12	pos	27
+p483.329T14	483.329	14	pos	28
+p483.365T13.3	483.365	13.3	pos	60
+p484.294T11.9	484.294	11.9	pos	51
+p484.369T13.3	484.369	13.3	pos	60
+p484.412T15.4	484.412	15.4	pos	74
+p485.348T16.3	485.348	16.3	pos	81
+p485.375T17.5	485.375	17.5	pos	92
+p489.229T6.5	489.229	6.5	pos	119
+p489.371T15.4	489.371	15.4	pos	74
+p493.411T16.7	493.411	16.7	pos	85
+p494.323T11.6	494.323	11.6	pos	49
+p494.44T16.7	494.44	16.7	pos	85
+p495.328T11.6	495.328	11.6	pos	49
+p495.445T16.7	495.445	16.7	pos	85
+p496.419T16.1	496.419	16.1	pos	79
+p496.457T16.7	496.457	16.7	pos	85
+p497.343T12.7	497.343	12.7	pos	56
+p498.902T0.8	498.902	0.8	pos	33
+p499.313T7.3	499.313	7.3	pos	126
+p499.346T16.2	499.346	16.2	pos	80
+p499.358T12.7	499.358	12.7	pos	56
+p500.363T12.7	500.363	12.7	pos	56
+p502.254T5.6	502.254	5.6	pos	111
+p503.337T15.4	503.337	15.4	pos	74
+p504.323T6.1	504.323	6.1	pos	115
+p504.346T13.1	504.346	13.1	pos	58
+p506.299T6.4	506.299	6.4	pos	118
+p508.34T12.4	508.34	12.4	pos	54
+p508.376T13.8	508.376	13.8	pos	63
+p509.38T13.8	509.38	13.8	pos	63
+p510.355T13.7	510.355	13.7	pos	62
+p510.434T15.4	510.434	15.4	pos	74
+p510.438T16.7	510.438	16.7	pos	85
+p511.441T16.7	511.441	16.7	pos	85
+p511.44T15.4	511.44	15.4	pos	74
+p512.443T15.4	512.443	15.4	pos	74
+p515.312T12.7	515.312	12.7	pos	56
+p515.388T16.7	515.388	16.7	pos	85
+p516.316T12.7	516.316	12.7	pos	56
+p516.337T7.3	516.337	7.3	pos	126
+p516.337T8	516.337	8	pos	24
+p516.397T16.7	516.397	16.7	pos	85
+p517.401T16.7	517.401	16.7	pos	85
+p518.325T12.7	518.325	12.7	pos	56
+p518.325T9.8	518.325	9.8	pos	144
+p520.332T12.1	520.332	12.1	pos	52
+p521.336T6.1	521.336	6.1	pos	115
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+p903.427T17.4	903.427	17.4	pos	91
+p906.468T15.9	906.468	15.9	pos	78
+p906.678T16.4	906.678	16.4	pos	82
+p906.787T8.5	906.787	8.5	pos	136
+p906.832T0.8	906.832	0.8	pos	33
+p91.056T1.4	91.056	1.4	pos	38
+p91.056T4.2	91.056	4.2	pos	102
+p911.63T16.4	911.63	16.4	pos	82
+p914.506T17.3	914.506	17.3	pos	90
+p916.446T16	916.446	16	pos	30
+p916.466T19.2	916.466	19.2	pos	99
+p918.45T16	918.45	16	pos	30
+p921.407T16	921.407	16	pos	30
+p923.408T16	923.408	16	pos	30
+p923.423T19.2	923.423	19.2	pos	99
+p924.41T16	924.41	16	pos	30
+p924.425T19.2	924.425	19.2	pos	99
+p926.35T7.2	926.35	7.2	pos	125
+p930.48T14.3	930.48	14.3	pos	64
+p930.498T17.3	930.498	17.3	pos	90
+p931.502T17.3	931.502	17.3	pos	90
+p932.5T17.3	932.5	17.3	pos	90
+p937.457T17.3	937.457	17.3	pos	90
+p938.459T17.3	938.459	17.3	pos	90
+p940.827T0.8	940.827	0.8	pos	33
+p944.524T15.9	944.524	15.9	pos	78
+p945.528T15.9	945.528	15.9	pos	78
+p946.445T17.4	946.445	17.4	pos	91
+p946.527T15.9	946.527	15.9	pos	78
+p947.469T16.5	947.469	16.5	pos	83
+p949.487T15.9	949.487	15.9	pos	78
+p950.469T7.5	950.469	7.5	pos	128
+p950.492T15.9	950.492	15.9	pos	78
+p955.657T16.4	955.657	16.4	pos	82
+p960.49T19.1	960.49	19.1	pos	98
+p961.495T19.1	961.495	19.1	pos	98
+p962.477T16	962.477	16	pos	30
+p962.495T19.1	962.495	19.1	pos	98
+p965.431T16	965.431	16	pos	30
+p965.447T19.1	965.447	19.1	pos	98
+p966.435T16	966.435	16	pos	30
+p966.693T14.8	966.693	14.8	pos	69
+p967.433T16	967.433	16	pos	30
+p967.449T19.1	967.449	19.1	pos	98
+p974.521T17.2	974.521	17.2	pos	89
+p975.525T17.2	975.525	17.2	pos	89
+p982.482T17.2	982.482	17.2	pos	89
+p988.545T15.9	988.545	15.9	pos	78
+p988.594T8.7	988.594	8.7	pos	137
+p989.547T15.9	989.547	15.9	pos	78
+p990.555T15.8	990.555	15.8	pos	77
+p990.796T0.8	990.796	0.8	pos	33
+p991.472T17.4	991.472	17.4	pos	91
+p991.659T12.7	991.659	12.7	pos	56
+p992.671T12.7	992.671	12.7	pos	56
+p995.427T17.4	995.427	17.4	pos	91
+p995.511T15.8	995.511	15.8	pos	77
+p995.7T12.7	995.7	12.7	pos	56
+p996.428T17.4	996.428	17.4	pos	91
+p999.669T16.4	999.669	16.4	pos	82
diff -r 000000000000 -r 58997c28b268 test-data/out_VM1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out_VM1.tabular	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,746 @@
+ions	mz	rt	mode	pcgroup	signal_moy	suppress
+p104.106T1	104.106	1	pos	21	228.792463078367	
+p459.279T6	459.279	6	pos	22	1187.46543831735	
+p476.304T6	476.304	6	pos	22	1087.84885746673	DEL
+p733.328T6	733.328	6	pos	22	402.482541466857	
+p477.309T6	477.309	6	pos	22	258.314933042551	DEL
+p105.033T6	105.033	6	pos	22	139.830213989592	
+p698.781T7	698.781	7	pos	23	291.089661149061	
+p814.485T7	814.485	7	pos	23	130.412929240653	
+p458.783T7	458.783	7	pos	23	42.8148096267959	DEL
+p560.365T8	560.365	8	pos	24	556.453990159673	
+p288.217T8	288.217	8	pos	24	423.776764993878	
+p516.337T8	516.337	8	pos	24	335.520032708837	DEL
+p565.321T8	565.321	8	pos	24	237.201671961082	DEL
+p534.32T10	534.32	10	pos	25	64.2696746977755	
+p380.256T11	380.256	11	pos	26	108.22666306551	
+p482.324T12	482.324	12	pos	27	1351.38193186531	
+p483.328T12	483.328	12	pos	27	383.73357776551	DEL
+p482.325T14	482.325	14	pos	28	688.149842746939	
+p464.314T14	464.314	14	pos	28	276.343929264694	DEL
+p483.329T14	483.329	14	pos	28	191.752925541633	DEL
+p790.588T15	790.588	15	pos	29	2165.21098979592	
+p795.551T15	795.551	15	pos	29	1765.01382289796	
+p834.612T15	834.612	15	pos	29	1187.15339670612	
+p796.553T15	796.553	15	pos	29	1002.61015956735	DEL
+p369.226T15	369.226	15	pos	29	195.340334717347	
+p326.167T15	326.167	15	pos	29	190.617773039388	DEL
+p863.624T15	863.624	15	pos	29	183.541343397755	
+p545.404T16	545.404	16	pos	30	1374.77036105102	
+p540.446T16	540.446	16	pos	30	1042.14513705918	
+p856.474T16	856.474	16	pos	30	843.846786909184	
+p861.434T16	861.434	16	pos	30	799.348960887306	DEL
+p584.474T16	584.474	16	pos	30	796.942577073469	
+p817.41T16	817.41	16	pos	30	732.566775253776	DEL
+p773.386T16	773.386	16	pos	30	693.613850636449	DEL
+p916.446T16	916.446	16	pos	30	687.139067537939	DEL
+p965.431T16	965.431	16	pos	30	661.837866280245	DEL
+p921.407T16	921.407	16	pos	30	634.900845126775	DEL
+p878.384T16	878.384	16	pos	30	557.296332678061	DEL
+p857.476T16	857.476	16	pos	30	515.988952367959	DEL
+p813.447T16	813.447	16	pos	30	506.831186415837	DEL
+p862.439T16	862.439	16	pos	30	458.873957280286	DEL
+p966.435T16	966.435	16	pos	30	438.870808196143	DEL
+p585.472T16	585.472	16	pos	30	313.562813302245	DEL
+p962.477T16	962.477	16	pos	30	299.221887681224	DEL
+p967.433T16	967.433	16	pos	30	292.733544446939	DEL
+p918.45T16	918.45	16	pos	30	289.179345494939	DEL
+p923.408T16	923.408	16	pos	30	259.865295644837	DEL
+p819.414T16	819.414	16	pos	30	236.311083521245	DEL
+p880.391T16	880.391	16	pos	30	163.790198722163	DEL
+p864.44T16	864.44	16	pos	30	140.902686981612	DEL
+p924.41T16	924.41	16	pos	30	115.876112963143	DEL
+p366.373T20	366.373	20	pos	31	110.582893822857	
+p214.916T0.7	214.916	0.7	pos	32	2027.46523106531	
+p84.962T0.7	84.962	0.7	pos	32	1137.79821322653	DEL
+p198.941T0.7	198.941	0.7	pos	32	796.866766192041	DEL
+p82.017T0.7	82.017	0.7	pos	32	345.973184404082	DEL
+p230.891T0.7	230.891	0.7	pos	32	317.168837654082	DEL
+p128.016T0.7	128.016	0.7	pos	32	291.965298265306	DEL
+p100.023T0.7	100.023	0.7	pos	32	85.8382465879592	DEL
+p151.033T0.7	151.033	0.7	pos	32	78.9029373334694	DEL
+p102.97T0.7	102.97	0.7	pos	32	50.7979220911633	DEL
+p226.952T0.8	226.952	0.8	pos	33	4221.94920361224	
+p430.913T0.8	430.913	0.8	pos	33	2111.16804065102	DEL
+p158.965T0.8	158.965	0.8	pos	33	2102.17244036122	DEL
+p702.864T0.8	702.864	0.8	pos	33	1587.26932115918	DEL
+p770.853T0.8	770.853	0.8	pos	33	1266.72590250612	DEL
+p838.842T0.8	838.842	0.8	pos	33	1249.51590616327	DEL
+p242.928T0.8	242.928	0.8	pos	33	1192.72531840816	
+p498.902T0.8	498.902	0.8	pos	33	887.771840238776	DEL
+p906.832T0.8	906.832	0.8	pos	33	845.415436506122	DEL
+p378.903T0.8	378.903	0.8	pos	33	704.116184518367	DEL
+p288.923T0.8	288.923	0.8	pos	33	698.11396715102	DEL
+p446.889T0.8	446.889	0.8	pos	33	498.422671291837	DEL
+p220.936T0.8	220.936	0.8	pos	33	403.150509636327	DEL
+p854.82T0.8	854.82	0.8	pos	33	340.06653134898	DEL
+p106.951T0.8	106.951	0.8	pos	33	302.30156072449	DEL
+p424.897T0.8	424.897	0.8	pos	33	298.943061525714	DEL
+p174.94T0.8	174.94	0.8	pos	33	293.739369267347	DEL
+p650.851T0.8	650.851	0.8	pos	33	275.60886777551	DEL
+p940.827T0.8	940.827	0.8	pos	33	198.192307551633	DEL
+p839.846T0.8	839.846	0.8	pos	33	191.972837024286	DEL
+p310.917T0.8	310.917	0.8	pos	33	190.312037754082	DEL
+p990.796T0.8	990.796	0.8	pos	33	190.168641453469	DEL
+p363.931T0.8	363.931	0.8	pos	33	187.384275485102	DEL
+p696.847T0.8	696.847	0.8	pos	33	161.668646117347	DEL
+p327.05T0.8	327.05	0.8	pos	33	149.058828805714	DEL
+p272.943T0.8	272.943	0.8	pos	33	138.222752395714	DEL
+p177.053T0.8	177.053	0.8	pos	33	117.445604064694	DEL
+p635.881T0.8	635.881	0.8	pos	33	115.314074500816	DEL
+p313.034T0.8	313.034	0.8	pos	33	94.5936623108163	DEL
+p228.957T0.8	228.957	0.8	pos	33	63.2101041689796	DEL
+p203.054T0.9	203.054	0.9	pos	34	1490.42755361429	
+p130.048T0.9	130.048	0.9	pos	34	354.502579959184	
+p219.082T0.9	219.082	0.9	pos	34	351.587567978367	
+p216.925T0.9	216.925	0.9	pos	34	342.551935789592	
+p84.048T0.9	84.048	0.9	pos	34	304.010665967347	DEL
+p175.116T0.9	175.116	0.9	pos	34	215.308230790408	DEL
+p207.024T0.9	207.024	0.9	pos	34	182.108326746735	
+p80.954T0.9	80.954	0.9	pos	34	173.214259318163	
+p200.034T0.9	200.034	0.9	pos	34	143.316717329592	DEL
+p150.01T0.9	150.01	0.9	pos	34	122.173238203469	DEL
+p204.057T0.9	204.057	0.9	pos	34	110.875659672041	DEL
+p196.87T0.9	196.87	0.9	pos	34	84.5217261270408	DEL
+p116.068T1.1	116.068	1.1	pos	35	729.022468679592	
+p70.07T1.1	70.07	1.1	pos	35	348.930551022449	DEL
+p254.976T1.1	254.976	1.1	pos	35	96.2933773	
+p189.086T1.2	189.086	1.2	pos	36	827.39712046551	
+p239.064T1.2	239.064	1.2	pos	36	294.024928340755	DEL
+p132.073T1.2	132.073	1.2	pos	36	236.723940043265	
+p90.056T1.2	90.056	1.2	pos	36	154.125281469796	DEL
+p276.12T1.2	276.12	1.2	pos	36	149.048537473469	
+p169.033T1.3	169.033	1.3	pos	37	1653.29833633265	
+p137.042T1.3	137.042	1.3	pos	37	384.983017360612	
+p185.027T1.3	185.027	1.3	pos	37	267.21573923249	
+p390.984T1.3	390.984	1.3	pos	37	214.212113813673	DEL
+p286.127T1.3	286.127	1.3	pos	37	162.755490917959	
+p170.032T1.3	170.032	1.3	pos	37	159.511540318776	DEL
+p247.139T1.3	247.139	1.3	pos	37	81.1804819897959	
+p150.057T1.3	150.057	1.3	pos	37	65.9994853691837	
+p73.087T1.3	73.087	1.3	pos	37	50.3682089265306	
+p148.06T1.3	148.06	1.3	pos	37	46.9045781104694	
+p326.126T1.3	326.126	1.3	pos	37	17.998813365	DEL
+p91.056T1.4	91.056	1.4	pos	38	39.3489777728571	
+p182.08T1.4	182.08	1.4	pos	38	39.1631336542857	
+p86.098T1.5	86.098	1.5	pos	39	356.204918563061	
+p119.047T1.5	119.047	1.5	pos	39	144.557150473265	
+p344.28T10.2	344.28	10.2	pos	40	164.666750170816	
+p255.16T10.2	255.16	10.2	pos	40	113.158205628163	
+p414.3T10.3	414.3	10.3	pos	41	740.141377142041	
+p432.311T10.3	432.311	10.3	pos	41	258.220775389388	DEL
+p272.259T10.3	272.259	10.3	pos	41	133.062720038367	
+p358.296T10.5	358.296	10.5	pos	42	87.5416363458775	
+p464.237T10.6	464.237	10.6	pos	43	56.5816749165918	
+p209.118T10.7	209.118	10.7	pos	44	931.698592730612	
+p286.144T10.9	286.144	10.9	pos	45	217.536063558347	
+p174.991T10.9	174.991	10.9	pos	45	76.9665620046939	
+p372.31T11.1	372.31	11.1	pos	46	132.608042339592	
+p468.308T11.2	468.308	11.2	pos	47	3154.65275690612	
+p469.312T11.2	469.312	11.2	pos	47	804.102175977551	DEL
+p470.316T11.2	470.316	11.2	pos	47	165.541834069184	DEL
+p305.304T11.3	305.304	11.3	pos	48	231.122682810204	
+p494.323T11.6	494.323	11.6	pos	49	3782.42301614286	
+p495.328T11.6	495.328	11.6	pos	49	1043.28803180408	DEL
+p424.342T11.7	424.342	11.7	pos	50	373.167461895918	
+p357.278T11.7	357.278	11.7	pos	50	366.243661892571	
+p478.297T11.9	478.297	11.9	pos	51	1875.54937203265	
+p526.294T11.9	526.294	11.9	pos	51	1208.49139871633	
+p479.298T11.9	479.298	11.9	pos	51	504.455663571429	DEL
+p484.294T11.9	484.294	11.9	pos	51	342.309654620408	
+p520.332T12.1	520.332	12.1	pos	52	22951.7023022449	
+p544.339T12.1	544.339	12.1	pos	52	7932.09912477551	
+p545.345T12.1	545.345	12.1	pos	52	2594.77731526531	DEL
+p568.34T12.1	568.34	12.1	pos	52	2311.71225347347	DEL
+p569.345T12.1	569.345	12.1	pos	52	779.549902112245	DEL
+p400.342T12.1	400.342	12.1	pos	52	519.701435383673	
+p546.346T12.1	546.346	12.1	pos	52	498.748958983469	
+p543.328T12.1	543.328	12.1	pos	52	418.047106031633	DEL
+p566.324T12.1	566.324	12.1	pos	52	322.933032671429	DEL
+p539.313T12.1	539.313	12.1	pos	52	296.920622848776	DEL
+p547.318T12.1	547.318	12.1	pos	52	264.421024477347	DEL
+p560.301T12.1	560.301	12.1	pos	52	237.242750191633	DEL
+p551.314T12.1	551.314	12.1	pos	52	172.387068239388	DEL
+p104.107T12.1	104.107	12.1	pos	52	135.858950144286	DEL
+p576.264T12.1	576.264	12.1	pos	52	131.133686113061	DEL
+p288.133T12.1	288.133	12.1	pos	52	79.173593192449	DEL
+p332.332T12.2	332.332	12.2	pos	53	391.265608553061	
+p184.073T12.4	184.073	12.4	pos	54	904.096973510204	
+p454.294T12.4	454.294	12.4	pos	54	753.936179904082	DEL
+p240.101T12.4	240.101	12.4	pos	54	561.625559663265	DEL
+p570.355T12.4	570.355	12.4	pos	54	430.505613614286	DEL
+p436.283T12.4	436.283	12.4	pos	54	411.812554195918	DEL
+p508.34T12.4	508.34	12.4	pos	54	347.549932971429	DEL
+p326.379T12.6	326.379	12.6	pos	55	2079.34282583673	
+p327.383T12.6	327.383	12.6	pos	55	537.471276632653	DEL
+p327.079T12.6	327.079	12.6	pos	55	347.632856696122	
+p548.361T12.6	548.361	12.6	pos	55	247.52146427551	
+p328.083T12.6	328.083	12.6	pos	55	81.9877778807551	DEL
+p991.659T12.7	991.659	12.7	pos	56	15469.9335488163	
+p497.343T12.7	497.343	12.7	pos	56	15360.5325767347	DEL
+p992.671T12.7	992.671	12.7	pos	56	9063.11881971429	DEL
+p518.325T12.7	518.325	12.7	pos	56	2439.60144867347	DEL
+p524.302T12.7	524.302	12.7	pos	56	1164.84250376122	
+p771.968T12.7	771.968	12.7	pos	56	675.10746487551	DEL
+p525.3T12.7	525.3	12.7	pos	56	618.550099197959	DEL
+p515.312T12.7	515.312	12.7	pos	56	598.484489538776	
+p499.358T12.7	499.358	12.7	pos	56	487.605918544898	
+p772.968T12.7	772.968	12.7	pos	56	452.086014589796	DEL
+p314.031T12.7	314.031	12.7	pos	56	306.275275761225	
+p104.107T12.7	104.107	12.7	pos	56	290.787125038776	DEL
+p770.967T12.7	770.967	12.7	pos	56	280.269913959184	DEL
+p135.023T12.7	135.023	12.7	pos	56	178.017150878959	DEL
+p534.301T12.7	534.301	12.7	pos	56	172.438531542857	DEL
+p995.7T12.7	995.7	12.7	pos	56	172.105494704898	DEL
+p500.363T12.7	500.363	12.7	pos	56	167.278736866735	
+p516.316T12.7	516.316	12.7	pos	56	133.859963186735	DEL
+p438.299T12.8	438.299	12.8	pos	57	580.235490530816	
+p523.359T13.1	523.359	13.1	pos	58	6691.91909702041	
+p544.34T13.1	544.34	13.1	pos	58	965.655247110204	DEL
+p504.346T13.1	504.346	13.1	pos	58	627.108811910204	DEL
+p551.314T13.1	551.314	13.1	pos	58	247.309423941429	DEL
+p810.991T13.1	810.991	13.1	pos	58	134.566070814286	DEL
+p179.143T13.1	179.143	13.1	pos	58	60.0390635247755	DEL
+p464.314T13.2	464.314	13.2	pos	59	377.856273520408	
+p482.359T13.3	482.359	13.3	pos	60	2027.42449276122	
+p483.365T13.3	483.365	13.3	pos	60	571.169895161225	DEL
+p303.233T13.3	303.233	13.3	pos	60	377.005709101959	DEL
+p484.369T13.3	484.369	13.3	pos	60	114.403502340816	DEL
+p304.238T13.3	304.238	13.3	pos	60	86.7779574130612	DEL
+p344.258T13.3	344.258	13.3	pos	60	54.2266942624286	DEL
+p548.372T13.6	548.372	13.6	pos	61	476.418687791837	
+p205.159T13.6	205.159	13.6	pos	61	21.2944781417959	DEL
+p510.355T13.7	510.355	13.7	pos	62	2100.94415358163	
+p149.02T13.7	149.02	13.7	pos	62	394.923868067347	
+p532.339T13.7	532.339	13.7	pos	62	193.36624214898	
+p276.055T13.7	276.055	13.7	pos	62	147.91428347551	
+p219.992T13.7	219.992	13.7	pos	62	107.879378272449	DEL
+p302.135T13.7	302.135	13.7	pos	62	106.298497653878	DEL
+p508.376T13.8	508.376	13.8	pos	63	1367.52210478571	
+p509.38T13.8	509.38	13.8	pos	63	408.654127330204	DEL
+p930.48T14.3	930.48	14.3	pos	64	155.558641438041	
+p886.459T14.4	886.459	14.4	pos	65	203.994428336306	
+p524.371T14.5	524.371	14.5	pos	66	3338.93711528571	
+p525.376T14.5	525.376	14.5	pos	66	1012.79454007347	DEL
+p466.332T14.5	466.332	14.5	pos	66	422.520135950612	DEL
+p798.414T14.5	798.414	14.5	pos	66	340.359946902857	DEL
+p842.433T14.5	842.433	14.5	pos	66	267.778455203204	DEL
+p799.413T14.5	799.413	14.5	pos	66	201.810272429592	DEL
+p800.42T14.5	800.42	14.5	pos	66	136.600766442306	DEL
+p826.439T14.5	826.439	14.5	pos	66	82.0288623577755	DEL
+p844.438T14.5	844.438	14.5	pos	66	80.1267063979796	DEL
+p385.292T14.6	385.292	14.6	pos	67	790.536564893878	
+p760.331T14.6	760.331	14.6	pos	67	382.862545894224	
+p407.335T14.6	407.335	14.6	pos	67	337.840935032653	
+p473.345T14.6	473.345	14.6	pos	67	323.94582567551	
+p364.326T14.6	364.326	14.6	pos	67	234.426171785714	
+p430.323T14.6	430.323	14.6	pos	67	169.611113214286	
+p715.303T14.6	715.303	14.6	pos	67	160.019947429939	
+p759.331T14.6	759.331	14.6	pos	67	135.621016790939	DEL
+p738.381T14.6	738.381	14.6	pos	67	111.634464628837	DEL
+p716.307T14.6	716.307	14.6	pos	67	78.5842410916326	DEL
+p712.351T14.6	712.351	14.6	pos	67	77.008369430898	DEL
+p756.394T14.6	756.394	14.6	pos	67	75.0307373284898	DEL
+p341.268T14.7	341.268	14.7	pos	68	620.54671034898	
+p300.289T14.7	300.289	14.7	pos	68	182.479694736735	
+p666.322T14.7	666.322	14.7	pos	68	150.278580450286	
+p671.278T14.7	671.278	14.7	pos	68	145.883068165551	DEL
+p627.249T14.7	627.249	14.7	pos	68	134.997710248918	DEL
+p628.255T14.7	628.255	14.7	pos	68	64.3463101012245	DEL
+p672.28T14.7	672.28	14.7	pos	68	56.9952304455714	DEL
+p629.251T14.7	629.251	14.7	pos	68	44.0580070385918	DEL
+p966.693T14.8	966.693	14.8	pos	69	232.66886237551	
+p251.048T14.8	251.048	14.8	pos	69	163.604915923469	
+p584.227T14.8	584.227	14.8	pos	69	84.4546984999184	
+p878.641T14.9	878.641	14.9	pos	70	775.496875930612	
+p879.644T14.9	879.644	14.9	pos	70	396.238958620408	
+p862.636T14.9	862.636	14.9	pos	70	365.623622797959	
+p707.495T15.1	707.495	15.1	pos	71	3576.43688328571	
+p746.564T15.1	746.564	15.1	pos	71	2804.05101189796	
+p703.548T15.1	703.548	15.1	pos	71	1995.68778918367	
+p747.571T15.1	747.571	15.1	pos	71	1118.31354159388	DEL
+p752.525T15.1	752.525	15.1	pos	71	1040.76789775102	DEL
+p774.593T15.1	774.593	15.1	pos	71	1031.89339762449	
+p723.47T15.1	723.47	15.1	pos	71	603.448599593878	DEL
+p619.44T15.2	619.44	15.2	pos	72	6310.85694918367	
+p658.509T15.2	658.509	15.2	pos	72	5466.42749930612	
+p663.467T15.2	663.467	15.2	pos	72	4636.10884644898	DEL
+p659.515T15.2	659.515	15.2	pos	72	2068.41538197959	DEL
+p664.471T15.2	664.471	15.2	pos	72	1741.59945326531	DEL
+p597.46T15.2	597.46	15.2	pos	72	1041.40014675714	DEL
+p643.519T15.2	643.519	15.2	pos	72	858.1587588	DEL
+p679.441T15.2	679.441	15.2	pos	72	727.870626134694	DEL
+p641.485T15.2	641.485	15.2	pos	72	643.704243744898	DEL
+p687.548T15.2	687.548	15.2	pos	72	603.996736869388	DEL
+p636.42T15.2	636.42	15.2	pos	72	322.103521073469	DEL
+p681.443T15.2	681.443	15.2	pos	72	136.529340332857	DEL
+p531.386T15.3	531.386	15.3	pos	73	9308.73894385714	
+p526.431T15.3	526.431	15.3	pos	73	8109.70821246939	DEL
+p570.458T15.3	570.458	15.3	pos	73	7878.81741132653	
+p575.414T15.3	575.414	15.3	pos	73	7557.59203244898	DEL
+p554.461T15.3	554.461	15.3	pos	73	4937.74203667347	DEL
+p598.488T15.3	598.488	15.3	pos	73	3353.19993526531	DEL
+p532.393T15.3	532.393	15.3	pos	73	2962.65702406122	DEL
+p571.463T15.3	571.463	15.3	pos	73	2714.69091722449	DEL
+p553.433T15.3	553.433	15.3	pos	73	1681.44712681837	DEL
+p599.495T15.3	599.495	15.3	pos	73	1167.46115630204	DEL
+p256.265T15.3	256.265	15.3	pos	73	1055.88803189388	
+p591.39T15.3	591.39	15.3	pos	73	944.09212592449	DEL
+p572.467T15.3	572.467	15.3	pos	73	628.447589908163	DEL
+p592.395T15.3	592.395	15.3	pos	73	320.073140122449	DEL
+p327.207T15.3	327.207	15.3	pos	73	272.641185173469	DEL
+p286.223T15.3	286.223	15.3	pos	73	264.158113816327	
+p257.267T15.3	257.267	15.3	pos	73	210.814245500408	DEL
+p443.333T15.4	443.333	15.4	pos	74	13783.568354551	
+p399.308T15.4	399.308	15.4	pos	74	12361.9126359796	
+p510.434T15.4	510.434	15.4	pos	74	6309.19904908163	
+p444.341T15.4	444.341	15.4	pos	74	3845.04461338775	DEL
+p400.314T15.4	400.314	15.4	pos	74	3160.36517261224	DEL
+p511.44T15.4	511.44	15.4	pos	74	1928.91788255102	DEL
+p467.412T15.4	467.412	15.4	pos	74	1665.91570995918	
+p356.288T15.4	356.288	15.4	pos	74	1438.82198174082	DEL
+p423.383T15.4	423.383	15.4	pos	74	1290.77557306122	DEL
+p338.344T15.4	338.344	15.4	pos	74	816.061759763265	
+p239.151T15.4	239.151	15.4	pos	74	740.505037379592	DEL
+p445.344T15.4	445.344	15.4	pos	74	727.972079718367	DEL
+p489.371T15.4	489.371	15.4	pos	74	712.952590444898	
+p503.337T15.4	503.337	15.4	pos	74	681.618482871429	DEL
+p89.062T15.4	89.062	15.4	pos	74	649.598560138775	DEL
+p401.316T15.4	401.316	15.4	pos	74	556.998515281633	DEL
+p459.311T15.4	459.311	15.4	pos	74	513.841945334694	DEL
+p283.178T15.4	283.178	15.4	pos	74	470.868221714286	DEL
+p379.341T15.4	379.341	15.4	pos	74	432.982780042857	
+p133.087T15.4	133.087	15.4	pos	74	415.190425177551	DEL
+p512.443T15.4	512.443	15.4	pos	74	375.372910836735	DEL
+p484.412T15.4	484.412	15.4	pos	74	341.939071581633	
+p439.381T15.4	439.381	15.4	pos	74	326.576592069388	DEL
+p177.115T15.4	177.115	15.4	pos	74	302.314306173469	DEL
+p371.258T15.4	371.258	15.4	pos	74	276.582901059184	DEL
+p271.264T15.4	271.264	15.4	pos	74	265.923248044898	DEL
+p357.289T15.4	357.289	15.4	pos	74	251.295786008163	DEL
+p424.386T15.4	424.386	15.4	pos	74	236.546562961224	DEL
+p334.303T15.4	334.303	15.4	pos	74	220.873825997959	DEL
+p315.291T15.4	315.291	15.4	pos	74	154.1874911	
+p196.129T15.4	196.129	15.4	pos	74	132.891567803061	DEL
+p107.072T15.4	107.072	15.4	pos	74	126.193713787143	
+p240.155T15.4	240.155	15.4	pos	74	110.049152267551	DEL
+p402.32T15.4	402.32	15.4	pos	74	101.815153112857	
+p269.232T15.5	269.232	15.5	pos	75	597.40947495102	
+p339.168T15.5	339.168	15.5	pos	75	346.384690826531	
+p328.285T15.5	328.285	15.5	pos	75	301.559409626531	DEL
+p353.265T15.5	353.265	15.5	pos	75	193.013596502449	
+p270.235T15.5	270.235	15.5	pos	75	141.576793466735	DEL
+p270.28T15.7	270.28	15.7	pos	76	385.609942279592	
+p995.511T15.8	995.511	15.8	pos	77	158.445806383673	
+p990.555T15.8	990.555	15.8	pos	77	146.078668213306	DEL
+p582.263T15.8	582.263	15.8	pos	77	69.0586275103673	DEL
+p604.278T15.8	604.278	15.8	pos	77	63.7880437446735	DEL
+p356.074T15.8	356.074	15.8	pos	77	45.2070091381429	DEL
+p900.488T15.9	900.488	15.9	pos	78	536.949711218327	
+p949.487T15.9	949.487	15.9	pos	78	503.629272733837	DEL
+p944.524T15.9	944.524	15.9	pos	78	486.018751860694	DEL
+p672.526T15.9	672.526	15.9	pos	78	423.93876721551	
+p988.545T15.9	988.545	15.9	pos	78	352.551784956776	DEL
+p901.489T15.9	901.489	15.9	pos	78	351.201016591041	DEL
+p950.492T15.9	950.492	15.9	pos	78	328.152047766367	DEL
+p906.468T15.9	906.468	15.9	pos	78	322.826505919184	DEL
+p945.528T15.9	945.528	15.9	pos	78	313.818176849388	DEL
+p989.547T15.9	989.547	15.9	pos	78	235.937190819306	DEL
+p902.496T15.9	902.496	15.9	pos	78	208.586017964694	DEL
+p946.527T15.9	946.527	15.9	pos	78	198.008899622653	DEL
+p560.246T15.9	560.246	15.9	pos	78	86.7854730425102	DEL
+p413.325T16.1	413.325	16.1	pos	79	3985.55671734694	
+p369.299T16.1	369.299	16.1	pos	79	3550.83163602041	
+p391.344T16.1	391.344	16.1	pos	79	1647.98324940816	DEL
+p436.394T16.1	436.394	16.1	pos	79	1453.44276849796	DEL
+p435.368T16.1	435.368	16.1	pos	79	1152.27589882041	DEL
+p872.42T16.1	872.42	16.1	pos	79	1115.0516449598	
+p828.395T16.1	828.395	16.1	pos	79	1044.46171554351	DEL
+p414.328T16.1	414.328	16.1	pos	79	1033.66624787755	DEL
+p458.354T16.1	458.354	16.1	pos	79	945.778077612245	DEL
+p370.301T16.1	370.301	16.1	pos	79	794.427707642857	DEL
+p496.419T16.1	496.419	16.1	pos	79	757.41400694898	DEL
+p724.397T16.1	724.397	16.1	pos	79	724.158979337878	DEL
+p784.372T16.1	784.372	16.1	pos	79	723.53710259598	DEL
+p561.415T16.1	561.415	16.1	pos	79	700.608927712245	
+p479.39T16.1	479.39	16.1	pos	79	654.805139028571	DEL
+p745.302T16.1	745.302	16.1	pos	79	567.044449323633	DEL
+p271.274T16.1	271.274	16.1	pos	79	477.771039502041	
+p769.412T16.1	769.412	16.1	pos	79	455.895050813347	DEL
+p347.31T16.1	347.31	16.1	pos	79	428.63405827551	DEL
+p785.377T16.1	785.377	16.1	pos	79	415.24328937851	DEL
+p641.312T16.1	641.312	16.1	pos	79	413.859129332041	DEL
+p481.399T16.1	481.399	16.1	pos	79	413.55078875102	DEL
+p437.393T16.1	437.393	16.1	pos	79	411.880202255102	DEL
+p685.334T16.1	685.334	16.1	pos	79	408.809226018163	DEL
+p328.316T16.1	328.316	16.1	pos	79	406.221193861224	
+p790.332T16.1	790.332	16.1	pos	79	388.335544233245	DEL
+p830.401T16.1	830.401	16.1	pos	79	384.820174924735	DEL
+p835.361T16.1	835.361	16.1	pos	79	336.184415376939	DEL
+p741.349T16.1	741.349	16.1	pos	79	314.663404871224	DEL
+p636.343T16.1	636.343	16.1	pos	79	305.949948277143	DEL
+p746.306T16.1	746.306	16.1	pos	79	299.41114948498	DEL
+p524.457T16.1	524.457	16.1	pos	79	285.321144255041	
+p770.414T16.1	770.414	16.1	pos	79	260.236963972306	DEL
+p681.374T16.1	681.374	16.1	pos	79	249.856108145204	DEL
+p726.4T16.1	726.4	16.1	pos	79	227.128041299388	DEL
+p686.334T16.1	686.334	16.1	pos	79	212.221908032306	DEL
+p371.286T16.1	371.286	16.1	pos	79	210.574661128367	
+p459.358T16.1	459.358	16.1	pos	79	203.677652796939	DEL
+p393.363T16.1	393.363	16.1	pos	79	202.529601571633	
+p731.365T16.1	731.365	16.1	pos	79	197.64525928351	DEL
+p742.348T16.1	742.348	16.1	pos	79	194.990386326878	DEL
+p525.458T16.1	525.458	16.1	pos	79	179.319128257082	
+p356.226T16.1	356.226	16.1	pos	79	176.791406306735	
+p427.358T16.1	427.358	16.1	pos	79	165.63846800551	
+p408.318T16.1	408.318	16.1	pos	79	162.091999887755	
+p682.372T16.1	682.372	16.1	pos	79	148.767336047898	DEL
+p643.311T16.1	643.311	16.1	pos	79	113.957502526306	
+p285.268T16.1	285.268	16.1	pos	79	111.210965472857	DEL
+p705.359T16.1	705.359	16.1	pos	79	92.1637976637143	DEL
+p849.327T16.1	849.327	16.1	pos	79	86.079937363	DEL
+p761.288T16.1	761.288	16.1	pos	79	50.8109587345306	DEL
+p465.329T16.2	465.329	16.2	pos	80	958.19181932449	
+p499.346T16.2	499.346	16.2	pos	80	732.146922765306	
+p593.362T16.2	593.362	16.2	pos	80	570.292630046939	
+p616.443T16.2	616.443	16.2	pos	80	359.253102154898	
+p702.282T16.2	702.282	16.2	pos	80	258.864863863122	
+p697.327T16.2	697.327	16.2	pos	80	199.239183796469	DEL
+p356.121T16.2	356.121	16.2	pos	80	176.992221190816	
+p355.077T16.2	355.077	16.2	pos	80	121.447161822347	DEL
+p189.098T16.2	189.098	16.2	pos	80	100.592347655918	DEL
+p532.328T16.2	532.328	16.2	pos	80	88.6690802182857	
+p586.434T16.3	586.434	16.3	pos	81	664.210485361225	
+p485.348T16.3	485.348	16.3	pos	81	599.866435393878	
+p455.333T16.3	455.333	16.3	pos	81	425.162314091837	
+p339.189T16.3	339.189	16.3	pos	81	294.698731279592	
+p466.334T16.3	466.334	16.3	pos	81	249.342798906122	
+p407.337T16.3	407.337	16.3	pos	81	243.960083936735	
+p341.216T16.3	341.216	16.3	pos	81	209.245221346939	
+p380.219T16.3	380.219	16.3	pos	81	159.567423346939	
+p911.63T16.4	911.63	16.4	pos	82	1172.25072590816	
+p955.657T16.4	955.657	16.4	pos	82	629.49899845102	
+p906.678T16.4	906.678	16.4	pos	82	533.118334316327	
+p999.669T16.4	999.669	16.4	pos	82	221.10386343449	
+p353.296T16.4	353.296	16.4	pos	82	183.575952091837	
+p779.55T16.5	779.55	16.5	pos	83	5535.94262042857	
+p823.577T16.5	823.577	16.5	pos	83	3795.78603961225	
+p780.555T16.5	780.555	16.5	pos	83	2428.83689061225	DEL
+p818.624T16.5	818.624	16.5	pos	83	1662.32718745306	DEL
+p775.601T16.5	775.601	16.5	pos	83	1221.96203291633	DEL
+p868.601T16.5	868.601	16.5	pos	83	902.47274857551	
+p819.625T16.5	819.625	16.5	pos	83	855.242255097959	DEL
+p862.654T16.5	862.654	16.5	pos	83	791.801492189796	
+p825.572T16.5	825.572	16.5	pos	83	623.538721259184	
+p846.654T16.5	846.654	16.5	pos	83	477.379016383673	
+p776.598T16.5	776.598	16.5	pos	83	430.487501738776	DEL
+p947.469T16.5	947.469	16.5	pos	83	142.993001389388	
+p843.939T16.5	843.939	16.5	pos	83	119.534593481918	DEL
+p647.469T16.6	647.469	16.6	pos	84	12474.9599371837	
+p603.444T16.6	603.444	16.6	pos	84	11930.0250487959	
+p642.516T16.6	642.516	16.6	pos	84	6813.98506138776	DEL
+p735.523T16.6	735.523	16.6	pos	84	6029.91072928571	DEL
+p648.478T16.6	648.478	16.6	pos	84	4808.53543622449	DEL
+p604.451T16.6	604.451	16.6	pos	84	4393.2363864898	DEL
+p692.504T16.6	692.504	16.6	pos	84	3961.15900346939	
+p626.522T16.6	626.522	16.6	pos	84	3195.26434208163	DEL
+p730.569T16.6	730.569	16.6	pos	84	3118.59456846939	DEL
+p670.549T16.6	670.549	16.6	pos	84	2664.64326677551	DEL
+p643.521T16.6	643.521	16.6	pos	84	2648.86350595918	DEL
+p736.529T16.6	736.529	16.6	pos	84	2519.34361091837	DEL
+p599.496T16.6	599.496	16.6	pos	84	2255.39160904082	DEL
+p714.576T16.6	714.576	16.6	pos	84	1795.20199642041	DEL
+p663.444T16.6	663.444	16.6	pos	84	1571.09644034131	
+p731.575T16.6	731.575	16.6	pos	84	1320.18388776939	DEL
+p649.482T16.6	649.482	16.6	pos	84	1184.93303823469	DEL
+p707.477T16.6	707.477	16.6	pos	84	1120.71651858163	DEL
+p605.458T16.6	605.458	16.6	pos	84	1062.59341866735	DEL
+p693.508T16.6	693.508	16.6	pos	84	1061.26729672653	DEL
+p715.576T16.6	715.576	16.6	pos	84	786.367788832653	DEL
+p650.486T16.6	650.486	16.6	pos	84	286.427658089796	DEL
+p800.429T16.6	800.429	16.6	pos	84	139.927451901449	
+p756.406T16.6	756.406	16.6	pos	84	124.791122729633	DEL
+p515.388T16.7	515.388	16.7	pos	85	18250.238182449	
+p559.416T16.7	559.416	16.7	pos	85	13665.4432377551	
+p427.337T16.7	427.337	16.7	pos	85	13154.0743199184	
+p538.468T16.7	538.468	16.7	pos	85	6558.46045759184	
+p494.44T16.7	494.44	16.7	pos	85	6241.68496381633	DEL
+p516.397T16.7	516.397	16.7	pos	85	6040.40313642857	DEL
+p472.372T16.7	472.372	16.7	pos	85	5742.12685095918	DEL
+p450.413T16.7	450.413	16.7	pos	85	4878.64760371429	DEL
+p560.425T16.7	560.425	16.7	pos	85	4787.74180067347	DEL
+p582.494T16.7	582.494	16.7	pos	85	4530.2486024898	DEL
+p510.438T16.7	510.438	16.7	pos	85	4108.18123565306	DEL
+p449.386T16.7	449.386	16.7	pos	85	3638.520236	DEL
+p428.346T16.7	428.346	16.7	pos	85	3588.66073744898	DEL
+p405.359T16.7	405.359	16.7	pos	85	3330.85106367347	DEL
+p493.411T16.7	493.411	16.7	pos	85	2737.49833869388	DEL
+p539.473T16.7	539.473	16.7	pos	85	2094.9353284898	DEL
+p495.445T16.7	495.445	16.7	pos	85	1889.37950765306	DEL
+p406.375T16.7	406.375	16.7	pos	85	1563.1563911449	DEL
+p583.5T16.7	583.5	16.7	pos	85	1559.71446663061	DEL
+p537.44T16.7	537.44	16.7	pos	85	1389.97308797959	DEL
+p384.32T16.7	384.32	16.7	pos	85	1359.25578242245	DEL
+p511.441T16.7	511.441	16.7	pos	85	1307.97217954286	DEL
+p517.401T16.7	517.401	16.7	pos	85	1210.27570276531	DEL
+p429.354T16.7	429.354	16.7	pos	85	853.132798866735	
+p556.472T16.7	556.472	16.7	pos	85	499.752795159184	DEL
+p540.475T16.7	540.475	16.7	pos	85	468.024612777551	DEL
+p361.333T16.7	361.333	16.7	pos	85	403.8259215	DEL
+p407.381T16.7	407.381	16.7	pos	85	344.411006171429	DEL
+p496.457T16.7	496.457	16.7	pos	85	274.193737426122	DEL
+p470.309T16.7	470.309	16.7	pos	85	191.517465977041	
+p734.394T16.7	734.394	16.7	pos	85	135.761528976735	
+p712.383T16.7	712.383	16.7	pos	85	120.40175633449	DEL
+p285.294T16.7	285.294	16.7	pos	85	104.504847194082	
+p759.879T16.7	759.879	16.7	pos	85	61.2648002122449	DEL
+p648.366T16.8	648.366	16.8	pos	86	181.801569706673	
+p671.33T16.8	671.33	16.8	pos	86	113.787862387408	DEL
+p703.871T16.8	703.871	16.8	pos	86	65.8185752610204	DEL
+p682.861T16.8	682.861	16.8	pos	86	38.4772573375714	DEL
+p626.317T16.9	626.317	16.9	pos	87	131.377787696878	
+p611.3T17.1	611.3	17.1	pos	88	133.214325835143	
+p974.521T17.2	974.521	17.2	pos	89	309.087268842469	
+p975.525T17.2	975.525	17.2	pos	89	223.956014589531	DEL
+p982.482T17.2	982.482	17.2	pos	89	122.333256958102	DEL
+p413.269T17.3	413.269	17.3	pos	90	2500.83888720408	
+p891.428T17.3	891.428	17.3	pos	90	841.287444223959	
+p414.273T17.3	414.273	17.3	pos	90	684.202788408163	DEL
+p848.406T17.3	848.406	17.3	pos	90	471.798861177	DEL
+p930.498T17.3	930.498	17.3	pos	90	390.128489975898	DEL
+p149.022T17.3	149.022	17.3	pos	90	387.014862685714	DEL
+p893.432T17.3	893.432	17.3	pos	90	344.230433954061	DEL
+p937.457T17.3	937.457	17.3	pos	90	335.062427517918	DEL
+p849.407T17.3	849.407	17.3	pos	90	293.925974645735	DEL
+p931.502T17.3	931.502	17.3	pos	90	267.19601325751	DEL
+p888.477T17.3	888.477	17.3	pos	90	192.928632522184	DEL
+p844.453T17.3	844.453	17.3	pos	90	173.898982961551	DEL
+p932.5T17.3	932.5	17.3	pos	90	171.458539887612	DEL
+p167.036T17.3	167.036	17.3	pos	90	154.965330019796	DEL
+p914.506T17.3	914.506	17.3	pos	90	154.531514982122	DEL
+p938.459T17.3	938.459	17.3	pos	90	150.032415177163	DEL
+p894.436T17.3	894.436	17.3	pos	90	143.22488034251	DEL
+p850.408T17.3	850.408	17.3	pos	90	124.751742388041	DEL
+p804.392T17.4	804.392	17.4	pos	91	499.588408910816	
+p715.327T17.4	715.327	17.4	pos	91	348.292014225224	DEL
+p995.427T17.4	995.427	17.4	pos	91	267.835675380592	DEL
+p671.311T17.4	671.311	17.4	pos	91	247.550418891694	DEL
+p805.389T17.4	805.389	17.4	pos	91	230.985401727735	DEL
+p761.358T17.4	761.358	17.4	pos	91	194.283069925857	DEL
+p996.428T17.4	996.428	17.4	pos	91	192.556995039551	DEL
+p716.328T17.4	716.328	17.4	pos	91	188.788335998347	DEL
+p799.428T17.4	799.428	17.4	pos	91	182.504918352	DEL
+p329.24T17.4	329.24	17.4	pos	91	152.343287806327	
+p946.445T17.4	946.445	17.4	pos	91	142.359083309449	DEL
+p672.315T17.4	672.315	17.4	pos	91	127.788693313102	DEL
+p738.408T17.4	738.408	17.4	pos	91	119.78011518598	DEL
+p902.424T17.4	902.424	17.4	pos	91	118.219452861306	DEL
+p991.472T17.4	991.472	17.4	pos	91	110.911472899653	DEL
+p710.383T17.4	710.383	17.4	pos	91	109.221263027653	DEL
+p711.394T17.4	711.394	17.4	pos	91	95.8634501904286	DEL
+p903.427T17.4	903.427	17.4	pos	91	87.1568874436122	DEL
+p756.402T17.4	756.402	17.4	pos	91	82.0927580574286	DEL
+p673.314T17.4	673.314	17.4	pos	91	78.9287234714286	DEL
+p485.375T17.5	485.375	17.5	pos	92	379.230990757143	
+p864.35T17.5	864.35	17.5	pos	92	149.197172690959	
+p627.292T17.5	627.292	17.5	pos	92	140.849789429306	DEL
+p731.276T17.5	731.276	17.5	pos	92	83.0753490668571	DEL
+p814.373T17.5	814.373	17.5	pos	92	76.469253925449	DEL
+p821.322T17.5	821.322	17.5	pos	92	75.1907869272449	DEL
+p628.278T17.5	628.278	17.5	pos	92	65.224558866102	DEL
+p733.276T17.6	733.276	17.6	pos	93	35.5179403750612	
+p585.273T17.8	585.273	17.8	pos	94	805.921230104082	
+p584.265T17.8	584.265	17.8	pos	94	530.999916004082	DEL
+p586.281T17.8	586.281	17.8	pos	94	270.579535286939	DEL
+p629.237T17.8	629.237	17.8	pos	94	105.746466062857	DEL
+p367.319T17.8	367.319	17.8	pos	94	57.6922578936735	
+p817.4T18.2	817.4	18.2	pos	95	264.955004136878	
+p839.906T18.2	839.906	18.2	pos	95	238.700812258347	DEL
+p796.39T18.2	796.39	18.2	pos	95	206.316927302571	DEL
+p862.426T18.2	862.426	18.2	pos	95	200.387686155918	DEL
+p815.423T18.2	815.423	18.2	pos	95	197.022411260388	DEL
+p826.414T18.2	826.414	18.2	pos	95	103.41969322551	DEL
+p773.377T18.3	773.377	18.3	pos	96	253.497139011673	
+p729.347T18.3	729.347	18.3	pos	96	228.991245948163	DEL
+p752.373T18.3	752.373	18.3	pos	96	189.108617994265	DEL
+p771.404T18.3	771.404	18.3	pos	96	183.990604477551	DEL
+p749.404T18.3	749.404	18.3	pos	96	173.495845407551	DEL
+p771.89T18.3	771.89	18.3	pos	96	120.975731061429	DEL
+p784.899T18.3	784.899	18.3	pos	96	84.005110374898	DEL
+p740.874T18.3	740.874	18.3	pos	96	64.0472726703061	DEL
+p707.339T18.4	707.339	18.4	pos	97	216.530570348082	
+p455.363T18.4	455.363	18.4	pos	97	192.382249183673	
+p705.394T18.4	705.394	18.4	pos	97	136.094928492102	DEL
+p686.325T18.4	686.325	18.4	pos	97	98.220323002	DEL
+p682.837T18.4	682.837	18.4	pos	97	59.7894374658163	DEL
+p965.447T19.1	965.447	19.1	pos	98	309.605332371122	
+p960.49T19.1	960.49	19.1	pos	98	162.046995657571	DEL
+p967.449T19.1	967.449	19.1	pos	98	158.081559896408	DEL
+p961.495T19.1	961.495	19.1	pos	98	121.072205957408	DEL
+p962.495T19.1	962.495	19.1	pos	98	84.8776259832857	DEL
+p878.397T19.2	878.397	19.2	pos	99	182.175218451449	
+p916.466T19.2	916.466	19.2	pos	99	155.979325833735	DEL
+p923.423T19.2	923.423	19.2	pos	99	145.450024227551	DEL
+p879.397T19.2	879.397	19.2	pos	99	128.592387337939	DEL
+p924.425T19.2	924.425	19.2	pos	99	74.4926853783673	DEL
+p835.371T19.3	835.371	19.3	pos	100	101.393625759898	
+p554.396T21.2	554.396	21.2	pos	101	601.307689873469	
+p136.072T4.2	136.072	4.2	pos	102	313.103129069388	
+p123.042T4.2	123.042	4.2	pos	102	275.366425262653	DEL
+p165.052T4.2	165.052	4.2	pos	102	215.559461812449	DEL
+p119.047T4.2	119.047	4.2	pos	102	191.297173423265	DEL
+p182.08T4.2	182.08	4.2	pos	102	90.7536038485714	DEL
+p276.145T4.2	276.145	4.2	pos	102	60.5311892511429	
+p137.048T4.2	137.048	4.2	pos	102	52.0051170916735	DEL
+p91.056T4.2	91.056	4.2	pos	102	48.2098975132041	DEL
+p326.149T4.2	326.149	4.2	pos	102	35.1187409929388	DEL
+p418.194T4.3	418.194	4.3	pos	103	289.505933468163	
+p194.117T4.3	194.117	4.3	pos	103	264.744330308163	
+p120.077T4.5	120.077	4.5	pos	104	4008.32824422449	
+p166.084T4.5	166.084	4.5	pos	104	554.064171571429	DEL
+p121.081T4.5	121.081	4.5	pos	104	420.055468918367	DEL
+p152.067T4.5	152.067	4.5	pos	104	211.795716820816	
+p131.046T4.5	131.046	4.5	pos	104	128.932226277959	DEL
+p149.057T4.5	149.057	4.5	pos	104	96.0019386022449	DEL
+p167.086T4.5	167.086	4.5	pos	104	70.885880577551	DEL
+p217.106T4.6	217.106	4.6	pos	105	667.044283942857	
+p310.13T4.6	310.13	4.6	pos	105	37.906712340449	DEL
+p192.136T4.7	192.136	4.7	pos	106	182.639065408163	
+p299.106T5.1	299.106	5.1	pos	107	341.736586807286	
+p555.296T5.1	555.296	5.1	pos	107	132.293439340224	
+p182.073T5.2	182.073	5.2	pos	108	58.729906981102	
+p189.073T5.3	189.073	5.3	pos	109	708.919594834694	
+p144.077T5.3	144.077	5.3	pos	109	296.435445912245	DEL
+p147.061T5.3	147.061	5.3	pos	109	221.544733163265	DEL
+p132.086T5.3	132.086	5.3	pos	109	165.461113704082	DEL
+p170.058T5.3	170.058	5.3	pos	109	116.681314817551	DEL
+p302.085T5.4	302.085	5.4	pos	110	354.07686134551	
+p627.571T5.6	627.571	5.6	pos	111	168.557479565306	
+p372.233T5.6	372.233	5.6	pos	111	141.687121803959	DEL
+p502.254T5.6	502.254	5.6	pos	111	115.551820527347	DEL
+p195.088T5.7	195.088	5.7	pos	112	1092.90421249086	
+p393.209T5.7	393.209	5.7	pos	112	566.640709153878	
+p388.253T5.7	388.253	5.7	pos	112	220.76041014002	
+p196.09T5.7	196.09	5.7	pos	112	128.717888536755	DEL
+p415.252T5.8	415.252	5.8	pos	113	1292.53388039122	
+p437.235T5.8	437.235	5.8	pos	113	887.612979386122	DEL
+p416.257T5.8	416.257	5.8	pos	113	263.18362473051	DEL
+p433.284T5.8	433.284	5.8	pos	113	119.200853893776	DEL
+p696.392T5.9	696.392	5.9	pos	114	329.772732195918	
+p697.398T5.9	697.398	5.9	pos	114	134.627563146939	DEL
+p189.022T6.1	189.022	6.1	pos	115	438.840778990816	
+p521.336T6.1	521.336	6.1	pos	115	371.618194039286	
+p188.027T6.1	188.027	6.1	pos	115	336.476061692735	
+p504.323T6.1	504.323	6.1	pos	115	264.630428712918	DEL
+p750.379T6.1	750.379	6.1	pos	115	262.407523465306	
+p207.053T6.1	207.053	6.1	pos	115	77.5326344772245	DEL
+p271.129T6.1	271.129	6.1	pos	115	62.045241948102	DEL
+p445.314T6.2	445.314	6.2	pos	116	314.627179438939	
+p564.357T6.3	564.357	6.3	pos	117	1051.62378104718	
+p569.315T6.3	569.315	6.3	pos	117	663.973953706653	DEL
+p547.333T6.3	547.333	6.3	pos	117	530.253959046082	DEL
+p565.363T6.3	565.363	6.3	pos	117	287.355229098388	DEL
+p279.17T6.3	279.17	6.3	pos	117	212.638885184673	
+p570.319T6.3	570.319	6.3	pos	117	175.487682990429	DEL
+p585.287T6.3	585.287	6.3	pos	117	103.374082044796	DEL
+p608.382T6.4	608.382	6.4	pos	118	1404.17647159204	
+p613.34T6.4	613.34	6.4	pos	118	772.213923930286	DEL
+p609.39T6.4	609.39	6.4	pos	118	420.270949208347	DEL
+p811.376T6.4	811.376	6.4	pos	118	246.862495441061	
+p592.374T6.4	592.374	6.4	pos	118	164.187888518061	DEL
+p636.404T6.4	636.404	6.4	pos	118	141.346799281898	DEL
+p664.332T6.4	664.332	6.4	pos	118	109.478721030571	DEL
+p506.299T6.4	506.299	6.4	pos	118	79.1243683054082	DEL
+p313.155T6.5	313.155	6.5	pos	119	2363.4707037588	
+p120.079T6.5	120.079	6.5	pos	119	937.561952290918	DEL
+p657.366T6.5	657.366	6.5	pos	119	576.061718492694	
+p314.16T6.5	314.16	6.5	pos	119	481.563899585673	DEL
+p864.411T6.5	864.411	6.5	pos	119	348.138344933061	DEL
+p550.326T6.5	550.326	6.5	pos	119	199.028334889041	DEL
+p489.229T6.5	489.229	6.5	pos	119	194.23152858749	DEL
+p166.086T6.5	166.086	6.5	pos	119	182.574429467061	DEL
+p658.372T6.5	658.372	6.5	pos	119	176.419866275286	DEL
+p555.281T6.5	555.281	6.5	pos	119	141.202556097653	DEL
+p418.193T6.5	418.193	6.5	pos	119	111.653404850082	DEL
+p340.18T6.5	340.18	6.5	pos	119	108.420034736633	DEL
+p673.341T6.5	673.341	6.5	pos	119	106.144757037959	DEL
+p121.082T6.5	121.082	6.5	pos	119	103.761077614122	DEL
+p680.432T6.5	680.432	6.5	pos	119	98.9682272312245	DEL
+p821.331T6.5	821.331	6.5	pos	119	79.7341045651429	DEL
+p551.329T6.5	551.329	6.5	pos	119	60.2107479865306	DEL
+p409.292T6.6	409.292	6.6	pos	120	952.361084335204	
+p696.437T6.6	696.437	6.6	pos	120	721.699714052796	
+p594.352T6.6	594.352	6.6	pos	120	304.879041930898	DEL
+p886.428T6.6	886.428	6.6	pos	120	299.999438268571	DEL
+p679.409T6.6	679.409	6.6	pos	120	182.504776745531	DEL
+p599.306T6.6	599.306	6.6	pos	120	167.180508630061	DEL
+p362.196T6.6	362.196	6.6	pos	120	126.057877954265	DEL
+p717.368T6.6	717.368	6.6	pos	120	66.3202173481837	DEL
+p643.334T6.7	643.334	6.7	pos	121	190.324942150429	
+p682.401T6.8	682.401	6.8	pos	122	384.179449173061	
+p687.361T6.8	687.361	6.8	pos	122	176.472290582143	DEL
+p726.429T6.9	726.429	6.9	pos	123	231.983408876429	
+p179.07T6.9	179.07	6.9	pos	123	117.56058680849	
+p731.387T6.9	731.387	6.9	pos	123	91.466443457551	DEL
+p239.09T7.1	239.09	7.1	pos	124	867.276769004082	
+p638.722T7.2	638.722	7.2	pos	125	247.493327524286	
+p472.311T7.2	472.311	7.2	pos	125	224.034891377082	
+p926.35T7.2	926.35	7.2	pos	125	117.754009675102	DEL
+p477.267T7.2	477.267	7.2	pos	125	108.434399742041	DEL
+p166.085T7.2	166.085	7.2	pos	125	94.7542653842245	DEL
+p455.285T7.2	455.285	7.2	pos	125	81.4542689129592	DEL
+p433.241T7.2	433.241	7.2	pos	125	78.0493571319388	DEL
+p611.239T7.2	611.239	7.2	pos	125	71.6841845536735	DEL
+p516.337T7.3	516.337	7.3	pos	126	364.028709477327	
+p286.202T7.3	286.202	7.3	pos	126	150.396608469796	
+p499.313T7.3	499.313	7.3	pos	126	91.4270760876122	DEL
+p565.32T7.4	565.32	7.4	pos	127	148.036597846633	
+p543.339T7.4	543.339	7.4	pos	127	90.9866627870816	DEL
+p430.302T7.4	430.302	7.4	pos	127	43.259151994	DEL
+p950.469T7.5	950.469	7.5	pos	128	137.003344521347	
+p609.347T7.5	609.347	7.5	pos	128	127.681077284163	DEL
+p776.561T7.6	776.561	7.6	pos	129	338.561139508163	
+p648.418T7.6	648.418	7.6	pos	129	102.421086619592	DEL
+p433.24T7.8	433.24	7.8	pos	130	85.5803787136122	
+p650.434T7.8	650.434	7.8	pos	130	83.6386007204082	DEL
+p472.311T7.9	472.311	7.9	pos	131	216.350951919878	
+p477.267T7.9	477.267	7.9	pos	131	164.664916745531	DEL
+p609.346T8.1	609.346	8.1	pos	132	222.380455616082	
+p610.348T8.1	610.348	8.1	pos	132	80.0874646119592	DEL
+p692.442T8.2	692.442	8.2	pos	133	431.039275736204	
+p648.418T8.2	648.418	8.2	pos	133	427.783405639775	DEL
+p653.374T8.2	653.374	8.2	pos	133	159.415907337388	DEL
+p693.448T8.2	693.448	8.2	pos	133	155.348215323388	DEL
+p698.404T8.2	698.404	8.2	pos	133	58.5280486199388	DEL
+p654.376T8.2	654.376	8.2	pos	133	49.3714192353061	DEL
+p780.498T8.3	780.498	8.3	pos	134	176.440415763061	
+p717.757T8.3	717.757	8.3	pos	134	82.344657380551	
+p815.486T8.4	815.486	8.4	pos	135	197.082168386633	
+p878.451T8.5	878.451	8.5	pos	136	403.439804625918	
+p906.787T8.5	906.787	8.5	pos	136	305.420454948898	DEL
+p759.886T8.5	759.886	8.5	pos	136	257.02326328198	
+p133.087T8.7	133.087	8.7	pos	137	373.570840752102	
+p221.14T8.7	221.14	8.7	pos	137	322.75079130651	DEL
+p89.062T8.7	89.062	8.7	pos	137	223.820676024571	DEL
+p723.438T8.7	723.438	8.7	pos	137	182.42439242998	DEL
+p146.095T8.7	146.095	8.7	pos	137	153.796084365571	DEL
+p679.413T8.7	679.413	8.7	pos	137	145.857816305265	DEL
+p213.233T8.7	213.233	8.7	pos	137	137.996252568163	
+p812.496T8.7	812.496	8.7	pos	137	122.737459154429	DEL
+p856.53T8.7	856.53	8.7	pos	137	113.073109287041	DEL
+p724.436T8.7	724.436	8.7	pos	137	109.197599606857	DEL
+p547.336T8.7	547.336	8.7	pos	137	92.4395170238776	DEL
+p648.39T8.7	648.39	8.7	pos	137	80.3491935941429	DEL
+p988.594T8.7	988.594	8.7	pos	137	73.8072649887959	DEL
+p73.037T8.7	73.037	8.7	pos	137	42.1988622891633	DEL
+p131.069T8.7	131.069	8.7	pos	137	27.9759834937755	DEL
+p75.185T8.9	75.185	8.9	pos	138	189.344382232816	
+p77.869T8.9	77.869	8.9	pos	138	169.570921054306	DEL
+p328.249T9.1	328.249	9.1	pos	139	161.789886974898	
+p317.253T9.1	317.253	9.1	pos	139	124.614849080286	
+p77.2T9.2	77.2	9.2	pos	140	1014.9694209898	
+p182.09T9.3	182.09	9.3	pos	141	131.403048735	
+p342.264T9.6	342.264	9.6	pos	142	157.499117578571	
+p240.233T9.7	240.233	9.7	pos	143	245.147764885714	
+p518.325T9.8	518.325	9.8	pos	144	772.278375773306	
+p194.098T9.8	194.098	9.8	pos	144	221.266501405102	
diff -r 000000000000 -r 58997c28b268 test-data/out_corr1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out_corr1.tabular	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,278 @@
+ions	rt	signal_moy	p104.106T1	p459.279T6	p733.328T6	p105.033T6	p698.781T7	p814.485T7	p560.365T8	p288.217T8	p534.32T10	p380.256T11	p482.324T12	p482.325T14	p790.588T15	p795.551T15	p834.612T15	p369.226T15	p863.624T15	p545.404T16	p540.446T16	p856.474T16	p584.474T16	p366.373T20	p214.916T0.7	p226.952T0.8	p242.928T0.8	p203.054T0.9	p130.048T0.9	p219.082T0.9	p216.925T0.9	p207.024T0.9	p80.954T0.9	p116.068T1.1	p254.976T1.1	p189.086T1.2	p132.073T1.2	p276.12T1.2	p169.033T1.3	p137.042T1.3	p185.027T1.3	p286.127T1.3	p247.139T1.3	p150.057T1.3	p73.087T1.3	p148.06T1.3	p91.056T1.4	p182.08T1.4	p86.098T1.5	p119.047T1.5	p344.28T10.2	p255.16T10.2	p414.3T10.3	p272.259T10.3	p358.296T10.5	p464.237T10.6	p209.118T10.7	p286.144T10.9	p174.991T10.9	p372.31T11.1	p468.308T11.2	p305.304T11.3	p494.323T11.6	p424.342T11.7	p357.278T11.7	p478.297T11.9	p526.294T11.9	p484.294T11.9	p520.332T12.1	p544.339T12.1	p400.342T12.1	p546.346T12.1	p332.332T12.2	p184.073T12.4	p326.379T12.6	p327.079T12.6	p548.361T12.6	p991.659T12.7	p524.302T12.7	p515.312T12.7	p499.358T12.7	p314.031T12.7	p500.363T12.7	p438.299T12.8	p523.359T13.1	p464.314T13.2	p482.359T13.3	p548.372T13.6	p510.355T13.7	p149.02T13.7	p532.339T13.7	p276.055T13.7	p508.376T13.8	p930.48T14.3	p886.459T14.4	p524.371T14.5	p385.292T14.6	p760.331T14.6	p407.335T14.6	p473.345T14.6	p364.326T14.6	p430.323T14.6	p715.303T14.6	p341.268T14.7	p300.289T14.7	p666.322T14.7	p966.693T14.8	p251.048T14.8	p584.227T14.8	p878.641T14.9	p879.644T14.9	p862.636T14.9	p707.495T15.1	p746.564T15.1	p703.548T15.1	p774.593T15.1	p619.44T15.2	p658.509T15.2	p531.386T15.3	p570.458T15.3	p256.265T15.3	p286.223T15.3	p443.333T15.4	p399.308T15.4	p510.434T15.4	p467.412T15.4	p338.344T15.4	p489.371T15.4	p379.341T15.4	p484.412T15.4	p315.291T15.4	p107.072T15.4	p402.32T15.4	p269.232T15.5	p339.168T15.5	p353.265T15.5	p270.28T15.7	p995.511T15.8	p900.488T15.9	p672.526T15.9	p413.325T16.1	p369.299T16.1	p872.42T16.1	p561.415T16.1	p271.274T16.1	p328.316T16.1	p524.457T16.1	p371.286T16.1	p393.363T16.1	p525.458T16.1	p356.226T16.1	p427.358T16.1	p408.318T16.1	p643.311T16.1	p465.329T16.2	p499.346T16.2	p593.362T16.2	p616.443T16.2	p702.282T16.2	p356.121T16.2	p532.328T16.2	p586.434T16.3	p485.348T16.3	p455.333T16.3	p339.189T16.3	p466.334T16.3	p407.337T16.3	p341.216T16.3	p380.219T16.3	p911.63T16.4	p955.657T16.4	p906.678T16.4	p999.669T16.4	p353.296T16.4	p779.55T16.5	p823.577T16.5	p868.601T16.5	p862.654T16.5	p825.572T16.5	p846.654T16.5	p947.469T16.5	p647.469T16.6	p603.444T16.6	p692.504T16.6	p663.444T16.6	p800.429T16.6	p515.388T16.7	p559.416T16.7	p427.337T16.7	p538.468T16.7	p429.354T16.7	p470.309T16.7	p734.394T16.7	p285.294T16.7	p648.366T16.8	p626.317T16.9	p611.3T17.1	p974.521T17.2	p413.269T17.3	p891.428T17.3	p804.392T17.4	p329.24T17.4	p485.375T17.5	p864.35T17.5	p733.276T17.6	p585.273T17.8	p367.319T17.8	p817.4T18.2	p773.377T18.3	p707.339T18.4	p455.363T18.4	p965.447T19.1	p878.397T19.2	p835.371T19.3	p554.396T21.2	p136.072T4.2	p276.145T4.2	p418.194T4.3	p194.117T4.3	p120.077T4.5	p152.067T4.5	p217.106T4.6	p192.136T4.7	p299.106T5.1	p555.296T5.1	p182.073T5.2	p189.073T5.3	p302.085T5.4	p627.571T5.6	p195.088T5.7	p393.209T5.7	p388.253T5.7	p415.252T5.8	p696.392T5.9	p189.022T6.1	p521.336T6.1	p188.027T6.1	p750.379T6.1	p445.314T6.2	p564.357T6.3	p279.17T6.3	p608.382T6.4	p811.376T6.4	p313.155T6.5	p657.366T6.5	p409.292T6.6	p696.437T6.6	p643.334T6.7	p682.401T6.8	p726.429T6.9	p179.07T6.9	p239.09T7.1	p638.722T7.2	p472.311T7.2	p516.337T7.3	p286.202T7.3	p565.32T7.4	p950.469T7.5	p776.561T7.6	p433.24T7.8	p472.311T7.9	p609.346T8.1	p692.442T8.2	p780.498T8.3	p717.757T8.3	p815.486T8.4	p878.451T8.5	p759.886T8.5	p133.087T8.7	p213.233T8.7	p75.185T8.9	p328.249T9.1	p317.253T9.1	p77.2T9.2	p182.09T9.3	p342.264T9.6	p240.233T9.7	p518.325T9.8	p194.098T9.8
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diff -r 000000000000 -r 58997c28b268 test-data/out_sif1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out_sif1.tabular	Tue Jan 19 16:41:47 2021 +0000
@@ -0,0 +1,3370 @@
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