--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml	Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,306 @@
+<macros>
+    <token name="@TOOL_VERSION@">1.2.2</token>
+
+    <xml name="creator">
+        <creator>
+            <person
+                givenName="Helge"
+                familyName="Hecht"
+                url="https://github.com/hechth"
+                identifier="0000-0001-6744-996X" />
+            <person
+                givenName="Maksym"
+                familyName="Skoryk"
+                url="https://github.com/maximskorik"
+                identifier="0000-0003-2056-8018" />
+            <person
+                givenName="Matej"
+                familyName="Troják"
+                url="https://github.com/xtrojak"
+                identifier="0000-0003-0841-2707" />
+            <person
+                givenName="Martin"
+                familyName="Čech"
+                url="https://github.com/martenson"
+                identifier="0000-0002-9318-1781" />
+            <organization
+                url="https://www.recetox.muni.cz/"
+                email="GalaxyToolsDevelopmentandDeployment@space.muni.cz"
+                name="RECETOX MUNI"/>
+        </creator>
+    </xml>
+
+    <xml name="parameters_csv">
+        <section name="ms_csv" title="Input MS Data as CSV" expanded="true">
+            <param label="Input CSV" name="ms" type="data" format="csv"
+                   help="Features as columns, rows as samples. Column header in format mz_rt."/>
+            <param label="idMSMS" name="idmsms" type="data" format="csv" optional="true"
+                   help="Optional idMSMS / MSe csv data. Same dimension and names as in input CSV are required."/>
+        </section>
+    </xml>
+
+    <xml name="parameters_xcms">
+        <section name="xcms" title="Input MS Data as XCMS" expanded="true">
+            <param name="input_xcms" label="Input XCMS" type="data" format="rdata.xcms.fillpeaks"
+                   help="Grouped feature data for clustering." />
+            <param label="Preserve phenotype" name="usePheno" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true"
+                   help="Transfer phenotype data from XCMS object to Spec abundance file."/>
+        </section>
+    </xml>
+
+    <xml name="parameters_required">
+        <param label="Sigma r" name="sr" type="float" value="0.5" help="Correlational similarity between features."/>
+        <param label="Correlation method" name="cor_method" type="select" display="radio"
+               help="Choose correlational method to be used - see [1] for details.">
+            <option value="pearson" selected="true">pearson</option>
+            <option value="everything">everything</option>
+            <option value="spearman">spearman</option>
+            <option value="kendall">kendall</option>
+        </param>
+        <param label="Maximum RT difference" name="maxt" value="60" type="float"
+               help="Maximum difference to calculate RT similarity - values beyond this are assigned zero similarity."/>
+    </xml>
+
+    <xml name="main_parameters">
+        <section name="clustering" title="Clustering" expanded="true">
+            <param label="Clustering linkage method" name="linkage" type="select" display="radio"
+                   help="Choose hierarchical clustering linkage method - see [2] for details.">
+                <option value="average" selected="true">average</option>
+                <option value="ward.D">ward.D</option>
+                <option value="ward.D2">ward.D2</option>
+                <option value="single">single</option>
+                <option value="complete">complete</option>
+                <option value="mcquitty">mcquitty</option>
+                <option value="median">median</option>
+                <option value="centroid">centroid</option>
+            </param>
+            <param label="Minimal cluster size" name="minModuleSize" type="integer" value="2"
+                   help="Minimal size (number of features) of a cluster."/>
+            <param label="Maximal tree height" name="hmax" type="float" value="0.3"
+                   help="Cut the Hierarchical Cluster Analysis tree at this height, see [3] for details."/>
+            <param label="Use deepSplit" name="deepSplit" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="false"
+                   help="Check to produce more smaller clusters, uncheck for fewer bigger clusters, see [3] for details."/>
+        </section>
+
+        <section name="normalisation" title="Normalisation" expanded="true">
+            <conditional name="normalisation_method">
+                <param label="Normalisation method" name="normalize" type="select" display="radio"
+                       help="Choose method for normalization of feature intensities.">
+                    <option value="none" selected="true">none</option>
+                    <option value="TIC">TIC</option>
+                    <option value="quantile">quantile</option>
+                    <option value="batch.qc">batch.qc</option>
+                </param>
+                <when value="batch.qc">
+                    <param label="Metadata details" name="batch_order_qc" type="data" format="csv" optional="true"
+                           help="CSV with sample names (or indices, currently not handled) on rows and columns with:
+                           batch number ('batch'), position in sequence ('order'), and whether it is a QC sample or not
+                           ('qc' with true/false OR 'sampleType' with 'sample/qc/blank')."/>
+                    <param label="QC injection range" name="qc_inj_range" type="integer" value="20"
+                             help="How many injections around each injection are to be scanned for presence of QC samples?
+                             A good rule of thumb is between 1 and 3 times the typical
+                             injection span between QC injections. i.e. if you inject QC ever 7 samples, set this to
+                             between 7 and 21. Smaller values provide more local precision but make normalization sensitive
+                             to individual poor outliers (though these are first removed using the boxplot function outlier
+                             detection), while wider values provide less local precision in normalization but better
+                             stability to individual peak areas."/>
+                </when>
+            </conditional>
+        </section>
+
+        <section name="performance" title="Performance">
+            <param label="Blocksize" name="blocksize" type="integer" value="2000"
+                   help="Number of features processed in one block."/>
+            <param label="Blocksize factor" name="mult" type="integer" value="5"
+                   help="Factor to scale blocksize to influence processing speed."/>
+        </section>
+
+        <section name="msp_output_details" title="MSP output">
+            <param label="Merge MSP Files" name="merge_msp" type="boolean" truevalue="TRUE" falsevalue="FALSE"
+                   checked="true" help="Merge all MSP in one file or export one MSP per spectra."/>
+            <param label="m/z decimal places" name="mzdec" type="integer" value="6"
+                   help="Number of decimal places used in printing m/z values."/>
+            <!--
+            Currently not forwarded because the MSP is exported always manually afterwards
+            <param label="mspout" name="mspout" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" help="write msp formatted spectra to file?" />
+            -->
+        </section>
+
+        <section name="extras" title="Extras">
+            <param label="RT only low n" name="rt_only_low_n" type="boolean" truevalue="TRUE" falsevalue="FALSE"
+                   checked="true"
+                   help="At low injection numbers, correlational relationships of peak intensities may be unreliable.
+                   By default, RAMClustR will simply ignore the correlational Sigma r value and cluster on retention time alone.
+                   If you wish to use correlation with at n less than 5, set this value to FALSE."/>
+            <param label="Replace zeros" name="replace_zeros" type="boolean" truevalue="TRUE" falsevalue="FALSE"
+                   checked="true"
+                   help="NA, NaN, and Inf values are replaced with zero, and zero values are sometimes returned from
+                   peak peaking. When TRUE, zero values will be replaced with a small amount of noise, with noise level
+                   set based on the detected signal intensities for that feature."/>
+            <param label="Experimental design metadata" name="ExpDes" type="data" format="csv" optional="true"
+                   help="Definition of experimental design in CSV format." />
+        </section>
+    </xml>
+
+    <xml name="output_msp">
+       <collection label="Mass spectra from ${tool.name} on ${on_string}" name="mass_spectra_collection" type="list">
+           <discover_datasets pattern="__name_and_ext__" directory="spectra" recurse="true" ext="msp"/>
+           <filter>not msp_output_details['merge_msp']</filter>
+       </collection>
+       <data label="Mass spectra from ${tool.name} on ${on_string}" name="mass_spectra_merged" format="msp">
+           <filter>msp_output_details['merge_msp']</filter>
+       </data>
+    </xml>
+
+    <xml name="citations">
+        <citations>
+            <!-- Example of annotating a citation using a BibTex entry. -->
+            <citation type="bibtex">
+                @article{Broeckling2014e,
+                abstract = {Metabolomic data are frequently acquired using chromatographically coupled mass spectrometry
+                (MS) platforms. For such datasets, the first step in data analysis relies on feature detection, where a
+                feature is defined by a mass and retention time. While a feature typically is derived from a single
+                compound, a spectrum of mass signals is more a more-accurate representation of the mass spectrometric
+                signal for a given metabolite. Here, we report a novel feature grouping method that operates in an
+                unsupervised manner to group signals from MS data into spectra without relying on predictability of the
+                in-source phenomenon. We additionally address a fundamental bottleneck in metabolomics, annotation of MS
+                level signals, by incorporating indiscriminant MS/MS (idMS/MS) data implicitly: feature detection is
+                performed on both MS and idMS/MS data, and feature-feature relationships are determined simultaneously
+                from the MS and idMS/MS data. This approach facilitates identification of metabolites using in-source MS
+                and/or idMS/MS spectra from a single experiment, reduces quantitative analytical variation compared to
+                single-feature measures, and decreases false positive annotations of unpredictable phenomenon as novel
+                compounds. This tool is released as a freely available R package, called RAMClustR, and is sufficiently
+                versatile to group features from any chromatographic-spectrometric platform or feature-finding software.
+                {\textcopyright} 2014 American Chemical Society.},
+                author = {Broeckling, C. D. and Afsar, F. A. and Neumann, S. and Ben-Hur, A. and Prenni, J. E.},
+                doi = {10.1021/ac501530d},
+                issn = {15206882},
+                journal = {Analytical Chemistry},
+                number = {14},
+                pages = {6812--6817},
+                pmid = {24927477},
+                title = {{RAMClust: A novel feature clustering method enables spectral-matching-based annotation for
+                metabolomics data}},
+                volume = {86},
+                year = {2014}
+                }
+            </citation>
+        </citations>
+    </xml>
+
+    <token name="@HELP@">
+        <![CDATA[
+            Documentation
+                    For documentation on the tool see https://github.com/cbroeckl/RAMClustR/blob/master/vignettes/RAMClustR.Rmd
+
+                Upstream Tools
+                    +------------------------------+-------------------------------+----------------------+---------------------+
+                    | Name                         | Output File                   | Format               | Parameter           |
+                    +==============================+===============================+======================+=====================+
+                    | xcms                         | xset.fillPeaks.RData          | rdata.xcms.fillpeaks | xcmsObj             |
+                    +------------------------------+-------------------------------+----------------------+---------------------+
+                    | RAMClustR define experiment  | Table with experiment details | csv                  | Experimental design |
+                    +------------------------------+-------------------------------+----------------------+---------------------+
+
+                    The tool takes an **xcmsSet** object as input and extracts all relevant information.
+
+                    +-------+------------------------+--------+------------+
+                    | Name  | Output File            | Format | Parameter  |
+                    +=======+========================+========+============+
+                    | ???   | Feature Table with MS1 | csv    | ms         |
+                    +-------+------------------------+--------+------------+
+                    | ???   | Feature Table with MS2 | csv    | idmsms     |
+                    +-------+------------------------+--------+------------+
+
+                    Alternatively, the tool takes a **csv** table as input which has to fulfill the following requirements
+
+                    (1) no more than one sample (or file) name column and one feature name row;
+                    (2) feature names that contain the mass and retention times, separated by a constant delimiter; and
+                    (3) features in columns and samples in rows.
+
+                    +----------------------+-------------------+-------------------+--------------------+--------------------+
+                    | sample               |    100.88_262.464 |    100.01_423.699 |    100.003_128.313 |   100.0057_154.686 |
+                    +======================+===================+===================+====================+====================+
+                    | 10_qc_16x_dil_milliq |    0              |    195953.6376	   |     0              |   0                |
+                    +----------------------+-------------------+-------------------+--------------------+--------------------+
+                    | 11_qc_8x_dil_milliq  |    0              |    117742.1828    |    4247300.664     |   0                |
+                    +----------------------+-------------------+-------------------+--------------------+--------------------+
+                    | 12_qc_32x_dil_milliq |    4470859.38     |    0              |    2206092.112     |   0                |
+                    +----------------------+-------------------+-------------------+--------------------+--------------------+
+                    | 15_qc_16x_dil_milliq |    0              |    0              |    2767477.481     |   0                |
+                    +----------------------+-------------------+-------------------+--------------------+--------------------+
+
+
+                Downstream Tools
+                    The output is a msp file or a collection of msp files, with additional Spec Abundance file.
+
+                    +---------+--------------+----------------------+
+                    | Name    | Output File  | Format               |
+                    +=========+==============+======================+
+                    | matchMS | Mass Spectra | collection (tgz/msp) |
+                    +---------+--------------+----------------------+
+
+        @GENERAL_HELP@
+        ]]>
+    </token>
+
+    <token name="@GENERAL_HELP@">
+        Background
+            Metabolomics
+                Metabolomics is frequently performed using chromatographically coupled mass spectrometry, with gas
+                chromatography, liquid chromatography, and capillary electrophoresis being the most frequently utilized
+                methods of separation. The coupling of chromatography to mass spectrometry is enabled with an
+                appropriate ionization source - electron impact (EI) for gas phase separations and electrospray
+                ionization (ESI) for liquid phase separations. XCMS is a commonly used tool to detect all the signals
+                from a metabolomics dataset, generating aligned features, where a feature is represented by a mass and
+                retention time. Each feature is presumed to derive from a single compound. However, each compound is
+                represented by several features. With any ionization method, isotopic peaks will be observed reflective
+                of the elemental composition of the analyte. In EI, fragmentation is a byproduct of ionization, and has
+                driven the generation of large mass spectral libraries. In ESI, in-source fragmentation frequently
+                occurs, the magnitude of which is compound dependent, with more labile compounds being more prone to
+                in-source fragmentation. ESI can also product multiple adduct forms (protonated, potassiated, sodiated,
+                ammoniated...), and can produce multimers (i.e. [2M+H]+, [3M+K]+, etc) and multiple charged species
+                ([M+2H]++). This can become further complicated by considering combinations of these phenomena. For
+                example [2M+3H]+++ (triply charged dimer) or an in-source fragment of a dimer.
+
+            RAMClustR approach
+                RAMClustR was designed to group features designed from the same compound using an approach which is
+                **1.** unsupervised, **2.** platform agnostic, and **3.** devoid of curated rules, as the depth of
+                understanding of these processes is insufficient to enable accurate curation/prediction of all phenomenon
+                that may occur. We achieve this by making two assumptions. The first is that two features derived
+                from the same compound with have (approximately) the same retention time. The second is that two
+                features derived from the same compound will have (approximately) the same quantitative trend across
+                all samples in the xcms sample set. From these assumptions, we can calculate a retention time
+                similarity score and a correlational similarity score for each feature pair. A high similarity score
+                for both retention time and correlation indicates a strong probability that two features derive from
+                the same compound. Since both conditions must be met, the product of the two similarity scores provides
+                the best approximation of the total similarity score - i.e. a feature pair with retention time similarity
+                of 1 and correlational similarity of 0 is unlikely to derive from one compound - 1 x 0 = 0, the final
+                similarity score is zero, indicating the two features represent two different compounds. Similarly, a
+                feature pair with retention time similarity of 0 and correlational similarity of 1 is unlikely to derive
+                from one compound - 0 x 1 = 0. Alternatively - a feature pair with retention time similarity of 1 and
+                correlational similarity of 1 is likely to derive from one compound - 1 x 1 = 1.
+
+        The RAMClustR algorithm is built on creating similarity scores for all pairs of features, submitting
+        this score matrix for hierarchical clustering, and then cutting the resulting dendrogram into neat
+        chunks using the dynamicTreeCut package - where each 'chunk' of the dendrogram results in a group of
+        features likely to be derived from a single compound. Importantly, this is achieved without looking for
+        specific phenomenon (i.e. sodiation), meaning that grouping can be performed on any dataset, whether it
+        is positive or negative ionization mode, EI or ESI, LC-MS GC-MS or CE-MS, in-source fragment or complex
+        adduction event, and predictable or unpredictable signals.
+    </token>
+
+        <token name="@HELP_experiment@">
+        <![CDATA[
+            Create an Experimental Design specification for RAMClustR experiment.
+
+            Downstream Tools
+                +-----------+-----------------------+--------+
+                | Name      | Output File           | Format |
+                +===========+=======================+========+
+                | RAMClustR | Experiment definition | csv    |
+                +-----------+-----------------------+--------+
+
+        ]]>
+    </token>
+</macros>

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ramclustr.xml	Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,175 @@
+<tool id="ramclustr" name="RAMClustR" version="@TOOL_VERSION@+galaxy2">
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="creator"/>
+
+    <requirements>
+        <requirement type="package" version="@TOOL_VERSION@">r-ramclustr</requirement>
+        <requirement type="package" version="3.14.0">bioconductor-xcms</requirement>
+    </requirements>
+
+    <command detect_errors="aggressive"><![CDATA[
+        Rscript
+            -e 'source("${__tool_directory__}/ramclustr_wrapper.R")'
+            -e 'source("${ramclustr_method}")'
+    ]]>
+    </command>
+    <configfiles>
+        <configfile name="ramclustr_method">
+            store_output(
+                #if $filetype.type_choice == "xcms":
+                ramclustr_xcms(
+                    input_xcms = "$filetype.xcms.input_xcms",
+                    use_pheno = $filetype.xcms.usePheno,
+                #else:
+                ramclustr_csv(
+                    ms = "$filetype.ms_csv.ms",
+                    idmsms = "$filetype.ms_csv.idmsms",
+                #end if
+                    sr = $filetype.required.sr,
+                    #if $filetype.type_choice == "xcms":
+                        #if $filetype.required.st
+                            st = $filetype.required.st,
+                        #end if
+                    #else:
+                        st = $filetype.required.st,
+                    #end if
+                    cor_method = "$filetype.required.cor_method",
+                    maxt = $filetype.required.maxt,
+                    linkage = "$clustering.linkage",
+                    min_module_size = $clustering.minModuleSize,
+                    hmax = $clustering.hmax,
+                    deep_split = "$clustering.deepSplit",
+                    normalize = "$normalisation.normalisation_method.normalize",
+                    #if "$normalisation.normalisation_method.normalize" == "batch.qc":
+                        metadata_file = "$normalisation.normalisation_method.batch_order_qc",
+                        qc_inj_range = $normalisation.normalisation_method.qc_inj_range,
+                    #end if
+                    block_size = $performance.blocksize,
+                    mult = $performance.mult,
+                    mzdec = $msp_output_details.mzdec,
+                    rt_only_low_n = $extras.rt_only_low_n,
+                    replace_zeros = $extras.replace_zeros,
+                    #if $extras.ExpDes:
+                        exp_design = "${$extras.ExpDes}"
+                    #end if
+                ),
+                $msp_output_details.merge_msp,
+                "$spec_abundance",
+            #if $msp_output_details.merge_msp:
+                "$mass_spectra_merged"
+            #else:
+                NULL
+            #end if
+                )
+        </configfile>
+    </configfiles>
+    <inputs>
+        <conditional name="filetype">
+            <param name="type_choice" type="select" label="Choose input format:">
+                <option value="xcms" selected="true">XCMS</option>
+                <option value="csv">CSV</option>
+            </param>
+            <when value="xcms">
+                <expand macro="parameters_xcms" />
+                <section name="required" title="General parameters" expanded="true">
+                    <param label="Sigma t" name="st" type="float" optional="true" help="Retention time similarity (optional).
+                           A recommended starting point is half the value of your average chromatographic peak width at half max (seconds))."/>
+                    <expand macro="parameters_required" />
+                </section>
+            </when>
+            <when value="csv">
+                <expand macro="parameters_csv" />
+                <section name="required" title="General parameters" expanded="true">
+                    <param label="Sigma t" name="st" type="float" value="1" help="Retention time similarity.
+                           A recommended starting point is half the value of your average chromatographic peak width at half max (seconds))."/>
+                    <expand macro="parameters_required" />
+                </section>
+            </when>
+        </conditional>
+        <expand macro="main_parameters" />
+    </inputs>
+
+    <outputs>
+        <data label="Spec Abundance of ${on_string}" name="spec_abundance" format="csv" />
+        <expand macro="output_msp"/>
+    </outputs>
+
+    <tests>
+        <test><!-- TEST 1 -->
+            <section name="filetype">
+                <param name="type_choice" value="xcms"/>
+                <section name="xcms">
+                    <param name="input_xcms" value="test1_xcmsObj_1.rdata.xcms.fillpeaks" ftype="rdata.xcms.fillpeaks"/>
+                </section>
+                <section name="required">
+                    <param name="maxt" value="259.8"/>
+                </section>
+            </section>
+            <section name="extras">
+                <param name="ExpDes" value="lc-ramclustr-define-experiment.csv" ftype="csv"/>
+            </section>
+            <output name="mass_spectra_merged" file="test1_fill_xcms_1.msp" ftype="msp"/>
+            <output name="spec_abundance" file="test1_spec_abundance_xcms_1.csv" ftype="csv" compare="sim_size" delta="100"/>
+        </test>
+        <test><!-- TEST 2 -->
+            <section name="filetype">
+                <param name="type_choice" value="xcms"/>
+                <section name="xcms">
+                    <param name="input_xcms" value="test2_xcmsObj_2.rdata.xcms.fillpeaks" ftype="rdata.xcms.fillpeaks"/>
+                </section>
+                <section name="required">
+                    <param name="maxt" value="78.4"/>
+                </section>
+            </section>
+            <section name="normalisation">
+                <section name="normalisation_method">
+                    <param name="batch_order_qc" value="test2_sample_metadata_xcms_2.csv" ftype="csv" />
+                </section>
+            </section>
+            <output name="mass_spectra_merged" file="test2_fill_xcms_2.msp" ftype="msp" compare="diff" lines_diff="10"/>
+            <output name="spec_abundance" file="test2_spec_abundance_xcms_2.csv" ftype="csv" compare="sim_size" delta="100"/>
+        </test>
+        <test><!-- TEST 3 -->
+            <section name="filetype">
+                <param name="type_choice" value="csv"/>
+                <section name="ms_csv">
+                    <param name="ms" value="test3_csv_test-input_1_2.csv" ftype="csv"/>
+                </section>
+                <section name="required">
+                    <param name="st" value="5.0"/>
+                    <param name="maxt" value="1"/>
+                </section>
+            </section>
+            <section name="performance">
+                <param name="blocksize" value="1000"/>
+                <param name="mult" value="1"/>
+            </section>
+            <output name="mass_spectra_merged" file="test3_spectra_csv_1.msp" ftype="msp"/>
+            <output name="spec_abundance" file="test3_spec_abundance_csv_1.csv" ftype="csv"/>
+        </test>
+        <test><!-- TEST 4 -->
+            <section name="filetype">
+                <param name="type_choice" value="csv"/>
+                <section name="ms_csv">
+                    <param name="ms" value="test3_csv_test-input_1_2.csv" ftype="csv"/>
+                </section>
+            </section>
+            <output name="mass_spectra_merged" file="test4_spectra_csv_2.msp" ftype="msp" lines_diff="10"/>
+        </test>
+    </tests>
+
+    <help>
+        <![CDATA[
+            @HELP@
+
+        .. rubric:: **Footnotes**
+        .. [1] Correlation, Variance and Covariance - `stats::cor <https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/cor>`_
+        .. [2] Hierarchical Clustering - `stats::hclust <https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/hclust>`_
+        .. [3] Dynamic Dendrogram Pruning Based on Dendrogram Only - `dynamicTreeCut::cutreeDynamicTree <https://www.rdocumentation.org/packages/dynamicTreeCut/versions/1.63-1/topics/cutreeDynamicTree>`_
+        ]]>
+    </help>
+
+    <expand macro="citations" />
+</tool>

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ramclustr_wrapper.R	Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,174 @@
+store_output <- function(
+    ramclustr_obj,
+    output_merge_msp,
+    output_spec_abundance,
+    msp_file) {
+    RAMClustR::write.msp(ramclustr_obj, one.file = output_merge_msp)
+    write.csv(ramclustr_obj$SpecAbund, file = output_spec_abundance, row.names = TRUE)
+
+    if (!is.null(msp_file)) {
+        exp.name <- ramclustr_obj$ExpDes[[1]][which(row.names(ramclustr_obj$ExpDes[[1]]) == "Experiment"), 1]
+        filename <- paste("spectra/", exp.name, ".msp", sep = "")
+        file.copy(from = filename, to = msp_file, overwrite = TRUE)
+    }
+}
+
+load_experiment_definition <- function(filename) {
+    experiment <- RAMClustR::defineExperiment(csv = filename)
+    return(experiment)
+}
+
+read_metadata <- function(filename) {
+    data <- read.csv(filename, header = TRUE, stringsAsFactors = FALSE)
+
+    if (!"qc" %in% colnames(data)) {
+        if ("sampleType" %in% colnames(data)) {
+            data$qc <- ifelse(data$sampleType == "qc", TRUE, FALSE)
+        }
+    }
+
+    if (!"order" %in% colnames(data)) {
+        if ("injectionOrder" %in% colnames(data)) {
+            names(data)[names(data) == "injectionOrder"] <- "order"
+        }
+    }
+
+    return(data)
+}
+
+ramclustr_xcms <- function(
+    input_xcms,
+    use_pheno,
+    sr,
+    st = NULL,
+    cor_method,
+    maxt,
+    linkage,
+    min_module_size,
+    hmax,
+    deep_split,
+    normalize,
+    metadata_file = NULL,
+    qc_inj_range,
+    block_size,
+    mult,
+    mzdec,
+    rt_only_low_n,
+    replace_zeros,
+    exp_design = NULL
+) {
+    obj <- load(input_xcms)
+
+    batch <- NULL
+    order <- NULL
+    qc <- NULL
+
+    if (!is.null(metadata_file)) {
+        metadata <- read_metadata(metadata_file)
+        batch <- metadata$batch
+        order <- metadata$order
+        qc <- metadata$qc
+    }
+
+    experiment <- NULL
+
+    if (!is.null(exp_design)) {
+        experiment <- load_experiment_definition(exp_design)
+    }
+
+    x <- RAMClustR::ramclustR(
+        xcmsObj = xdata,
+        st = st,
+        maxt = maxt,
+        sr = sr,
+        deepSplit = deep_split,
+        blocksize = block_size,
+        mult = mult,
+        hmax = hmax,
+        usePheno = use_pheno,
+        mspout = FALSE,
+        qc.inj.range = qc_inj_range,
+        normalize = normalize,
+        minModuleSize = min_module_size,
+        linkage = linkage,
+        mzdec = mzdec,
+        cor.method = cor_method,
+        rt.only.low.n = rt_only_low_n,
+        fftempdir = NULL,
+        replace.zeros = replace_zeros,
+        batch = batch,
+        order = order,
+        qc = qc,
+        ExpDes = experiment
+        )
+    return(x)
+}
+
+ramclustr_csv <- function(
+    ms,
+    idmsms,
+    sr,
+    st,
+    cor_method,
+    maxt,
+    linkage,
+    min_module_size,
+    hmax,
+    deep_split,
+    normalize,
+    metadata_file = NULL,
+    qc_inj_range,
+    block_size,
+    mult,
+    mzdec,
+    rt_only_low_n,
+    replace_zeros,
+    exp_design = NULL
+) {
+    if (!file.exists(idmsms))
+        idmsms <- NULL
+
+    batch <- NULL
+    order <- NULL
+    qc <- NULL
+
+    if (!is.null(metadata_file)) {
+        metadata <- read_metadata(metadata_file)
+        batch <- metadata$batch
+        order <- metadata$order
+        qc <- metadata$qc
+    }
+
+    experiment <- NULL
+
+    if (!is.null(exp_design)) {
+        experiment <- load_experiment_definition(exp_design)
+    }
+
+    x <- RAMClustR::ramclustR(
+        ms = ms,
+        idmsms = idmsms,
+        st = st,
+        maxt = maxt,
+        sr = sr,
+        deepSplit = deep_split,
+        blocksize = block_size,
+        mult = mult,
+        hmax = hmax,
+        mspout = FALSE,
+        qc.inj.range = qc_inj_range,
+        normalize = normalize,
+        minModuleSize = min_module_size,
+        linkage = linkage,
+        mzdec = mzdec,
+        cor.method = cor_method,
+        rt.only.low.n = rt_only_low_n,
+        fftempdir = NULL,
+        replace.zeros = replace_zeros,
+        batch = batch,
+        order = order,
+        qc = qc,
+        ExpDes = experiment
+        )
+        return(x)
+}

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/gc-ramclustr-define-experiment.csv	Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,38 @@
+parameter,Value,Description
+,,
+Experimental Design,,
+Experiment,experiment_gc,"Experiment name, no spaces."
+Species,mus musculus,Genus species from which samples are derived.
+Sample,serum,"Type of sample (e.g., serum, leaf)."
+Contributer,recetox,Your or your PI's name.
+platform,GC-MS,Either GC-MS or LC-MS.
+,,
+GC-MS,,
+chrominst,ISQ 7000,Model of LC/GC instrument.
+msinst,ISQ7K-VPI,Model of MS instrument.
+column,These columns enable analysis of ppm levels of amines without column priming,Column description.
+InletTemp,33,Temperature of inlet.
+TransferTemp,23,Temperature of GC to MS transfer line.
+mstype,QTOF,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,positive,Positive or negative ion mode.
+ionization,AP,"Ionization (EI, AP, or CI)."
+msscanrange,100,Scan range used for acquisition.
+scantime,0.2,Time for each full scan spectrum (e.g. 0.2 seconds).
+deriv,TMS,"Derivitization (TMS, TBDMS, or None)."
+MSlevs,1.0,Number of levels of energy acquired - 1 typically.
+,,
+LC-MS,,
+chrominst,fill,Model of LC/GC instrument.
+msinst,fill,Model of MS instrument.
+column,fill,Column description.
+solvA,fill,Solvent A composition.
+solvB,fill,Solvent B composition.
+CE1,fill,Collision energy of acquisition of MS data.
+CE2,fill,Collision energy of acquisition for MSe/idMSMS data (when applicable).
+mstype,fill,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,fill,Positive or negative ion mode.
+ionization,fill,"Ionization (EI, AP, or CI)."
+colgas,fill,Gas used for collisional dissociation.
+msscanrange,fill,Scan range used for acquisition.
+conevol,fill,Cone voltage used for acquisition.
+MSlevs,fill,Number of levels of energy acquired - 1 typically.

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/lc-ramclustr-define-experiment.csv	Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,38 @@
+parameter,Value,Description
+,,
+Experimental Design,,
+Experiment,experiment_lc,"Experiment name, no spaces."
+Species,mus musculus,Genus species from which samples are derived.
+Sample,serum,"Type of sample (e.g., serum, leaf)."
+Contributer,recetox,Your or your PI's name.
+platform,LC-MS,Either GC-MS or LC-MS.
+,,
+GC-MS,,
+chrominst,fill,Model of LC/GC instrument.
+msinst,fill,Model of MS instrument.
+column,fill,Column description.
+InletTemp,fill,Temperature of inlet.
+TransferTemp,fill,Temperature of GC to MS transfer line.
+mstype,fill,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,fill,Positive or negative ion mode.
+ionization,fill,"Ionization (EI, AP, or CI)."
+msscanrange,fill,Scan range used for acquisition.
+scantime,fill,Time for each full scan spectrum (e.g. 0.2 seconds).
+deriv,fill,"Derivitization (TMS, TBDMS, or None)."
+MSlevs,fill,Number of levels of energy acquired - 1 typically.
+,,
+LC-MS,,
+chrominst,UltiMateX 3000 BioRS System,Model of LC/GC instrument.
+msinst,FSN04-10000,Model of MS instrument.
+column,These columns enable analysis of ppm levels of amines without column priming,Column description.
+solvA,H20,Solvent A composition.
+solvB,CO2,Solvent B composition.
+CE1,50,Collision energy of acquisition of MS data.
+CE2,100,Collision energy of acquisition for MSe/idMSMS data (when applicable).
+mstype,Q,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,negative,Positive or negative ion mode.
+ionization,ESI,"Ionization (EI, AP, or CI)."
+colgas,He,Gas used for collisional dissociation.
+msscanrange,1000,Scan range used for acquisition.
+conevol,12,Cone voltage used for acquisition.
+MSlevs,1.0,Number of levels of energy acquired - 1 typically.

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test1_fill_xcms_1.msp	Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,1991 @@
+NAME:C001
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:38.74
+Num Peaks:57
+216.9205 32607700
+256.8215 31377637
+175.0641 26780143
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+
+NAME:C002
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:520.25
+Num Peaks:35
+525.375 1073323842
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+
+NAME:C003
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+RETENTIONTIME:483.67
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+
+NAME:C004
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:473.48
+Num Peaks:24
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+
+NAME:C005
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:41.72
+Num Peaks:20
+337.0623 88672453
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+
+NAME:C006
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+RETENTIONTIME:452.08
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+IONMODE:Negative
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+Num Peaks:9
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test1_spec_abundance_xcms_1.csv	Tue Mar 22 16:09:16 2022 +0000
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Binary file test-data/test1_xcmsObj_1.rdata.xcms.fillpeaks has changed

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test2_fill_xcms_2.msp	Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,11378 @@
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