Mercurial > repos > ethevenot > profia
diff profia_config.xml @ 0:39ccace77270 draft
planemo upload for repository https://github.com/workflow4metabolomics/profia.git commit 2757590af8c7ba9833ba3bebd7da7f96b20d1128-dirty
author | ethevenot |
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date | Sun, 26 Mar 2017 17:37:12 -0400 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/profia_config.xml Sun Mar 26 17:37:12 2017 -0400 @@ -0,0 +1,283 @@ +<tool id="profia" name="proFIA" version="3.0.0"> + <description>Preprocessing of FIA-HRMS data</description> + + <requirements> + <requirement type="package">r-batch</requirement> + <requirement type="package">r-FNN</requirement> + <requirement type="package">r-maxLik</requirement> + <requirement type="package">r-minpack.lm</requirement> + <requirement type="package">r-pracma</requirement> + <requirement type="package">bioconductor-proFIA</requirement> + </requirements> + + <stdio> + <exit_code range="1:" level="fatal" /> + </stdio> + + <command><![CDATA[ + Rscript $__tool_directory__/profia_wrapper.R + + #if $inputs.input == "lib": + library $__app__.config.user_library_import_dir/$__user_email__/$inputs.library + #elif $inputs.input == "zip_file": + zipfile $inputs.zip_file + #end if + + ppmN "$ppmN" + ppmGroupN "$ppmGroupN" + fracGroupN "$fracGroupN" + kI "$kI" + + dataMatrix_out "$dataMatrix_out" + sampleMetadata_out "$sampleMetadata_out" + variableMetadata_out "$variableMetadata_out" + figure "$figure" + information "$information" + ]]></command> + + <inputs> + <conditional name="inputs"> + <param name="input" type="select" label="Choose your input method" > + <option value="zip_file" selected="true">Zip file from your history containing your raw files</option> + <option value="lib" >Library directory name</option> + </param> + <when value="zip_file"> + <param name="zip_file" type="data" format="no_unzip.zip,zip" label="Zip file" /> + </when> + <when value="lib"> + <param name="library" type="text" size="40" label="Library directory name" help="The name of your directory containing all your data" > + <validator type="empty_field"/> + </param> + </when> + </conditional> + + <param name="ppmN" label="Maximum deviation between centroids during band detection (in ppm)" type="text" value = "5" help="[ppm]" /> + <param name="ppmGroupN" label="Accuracy of the mass spectrometer to be used during feature alignment (in ppm)" type="text" value = "5" help="[ppmGroup] Should be inferior or equal to the deviation parameter above." /> + <param name="fracGroupN" label=" Minimum fraction of samples in which a peak should be detected in at least one class to be kept during feature alignment" type="text" value = "0.5" help="[fracGroup]" /> + <param name="kI" label="Number of neighbour features to be used for imputation (select 0 to skip the imputation step)" type="text" value = "5" help="[k]" /> + </inputs> + + <outputs> + <data name="dataMatrix_out" label="${tool.name}_dataMatrix.tsv" format="tabular" ></data> + <data name="sampleMetadata_out" label="${tool.name}_sampleMetadata.tsv" format="tabular" ></data> + <data name="variableMetadata_out" label="${tool.name}_variableMetadata.tsv" format="tabular" ></data> + <data name="figure" label="${tool.name}_figure.pdf" format="pdf"/> + <data name="information" label="${tool.name}_information.txt" format="txt"/> + </outputs> + + <tests> + <test> + <param name="inputs|input" value="zip_file" /> + <param name="inputs|zip_file" value="input-plasFIA.zip" ftype="zip" /> + <param name="ppmN" value="2"/> + <param name="ppmGroupN" value="1"/> + <param name="fracGroupN" value="0.1"/> + <param name="kI" value="2"/> + <output name="dataMatrix_out" file="output-dataMatrix.tsv"/> + </test> + </tests> + + <help> + +.. class:: infomark + +**Author** Alexis Delabriere and Etienne Thevenot (CEA, LIST, MetaboHUB Paris, etienne.thevenot@cea.fr) + +--------------------------------------------------- + +.. class:: infomark + +**Please cite** + +Delabriere A., Hohenester U., Junot C. and Thevenot E.A. *proFIA*: A data preprocessing workflow for Flow Injection Analysis coupled to High-Resolution Mass Spectrometry. *submitted*. + +--------------------------------------------------- + +.. class:: infomark + +**R package** + +The **proFIA** package is available from the bioconductor repository `http://bioconductor.org/packages/proFIA <http://bioconductor.org/packages/proFIA>`_ + +--------------------------------------------------- + +.. class:: infomark + +**Tool updates** + +See the **NEWS** section at the bottom of this page + +--------------------------------------------------- + +========================================================== +*proFIA*: Preprocessing workflow for FIA-HRMS data +========================================================== + +----------- +Description +----------- + +**Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS)** is a promising approach for **high-throughput metabolomics** (Madalinski *et al.*, 2008; Fuhrer *et al.*, 2011; Draper *et al.*, 2013). FIA- HRMS data, however, cannot be preprocessed with current software tools which rely on liquid chromatography separation, or handle low resolution data only. + +The **proFIA module is a workflow** allowing to preprocess FIA-HRMS raw data in **centroid** mode and open format (netCDF, mzData, mzXML, and mzML), and generates the table of peak intensities (**peak table**). The workflow consists in **peak detection and quantification** within individual sample files, followed by **alignment** between files in the m/z dimension, and **imputation** of the missing values in the final peak table (Delabriere *et al.*, submitted). For each ion, the graph representing the intensity as a function of time is called a **flowgram**. A flowgram can be modeled as I = kP + ME(P) + B + e, where k is the response factor (corresponding to the ionization properties of the analyte), P is the **sample peak** (normalized profile which is common for all analytes from a sample and depends on the flow injection conditions only), ME is the **matrix effect**, B is the **solvent baseline**, and e is the heteroscedastic noise. + +The generated peak table is available in the '3 table' W4M tabular format (**dataMatrix**, **sampleMetadata**, and **variableMetadata**) for downstream statistical analysis and annotation with W4M modules. + +A figure provides **diagnostics** and visualization of the preprocessed data set. + +--------------------------------------------------- + +.. class:: infomark + +**References** + +| Delabriere A., Hohenester U., Junot C. and Thevenot E.A. proFIA: A data preprocessing workflow for Flow Injection Analysis coupled to High-Resolution Mass Spectrometry. *submitted*. +| Draper J., Lloyd A., Goodacre R. and Beckmann M. (2013). Flow infusion electrospray ionisation mass spectrometry for high throughput, non-targeted metabolite fingerprinting: a review. *Metabolomics* 9, 4-29. +| Fuhrer T., Dominik H., Boris B. and Zamboni N. (2011). High-throughput, accurate mass metabolome profiling of cellular extracts by flow injection-time-of-flight mass spectrometry. *Analytical Chemistry* 83, 7074-7080. +| Madalinski G., Godat E., Alves S., Lesage D., Genin E., Levi P., Labarre J., Tabet J., Ezan E. and Junot, C. (2008). Direct introduction of biological samples into a LTQ-orbitrap hybrid mass spectrometer as a tool for fast metabolome analysis. *Analytical Chemistry* 80, 3291-3303. + +--------------------------------------------------- + +----------------- +Workflow position +----------------- + +.. image:: profia_workflowPositionImage.png + :width: 600 + +----------- +Input files +----------- + ++---------------------------+------------+ +| Parameter : num + label | Format | ++===========================+============+ +| 1 : Choose your inputs | zip | ++---------------------------+------------+ + + +You have two methods for your inputs: + | Zip file (recommended): You can put a zip file containing your inputs: myinputs.zip (containing all your conditions as sub-directories). + | library folder: You must specify the name of your "library" (folder) created within your space project (for example: /projet/externe/institut/login/galaxylibrary/yourlibrary). Your library must contain all your conditions as sub-directories. + +**Steps for creating the zip file** + +**Step1: Creating your directory and hierarchize the subdirectories** + +.. class:: warningmark + +VERY IMPORTANT: If you zip your files under Windows, you must use the **7Zip** software (http://www.7-zip.org/), otherwise your zip will not be well unzipped on the platform W4M (zip corrupted bug). +Your zip should contain all your conditions as sub-directories. For example, two conditions (mutant and wild): +arabidopsis/wild/01.raw +arabidopsis/mutant/01.raw + +**Step2: Creating a zip file** +Create your zip file (e.g.: arabidopsis.zip). + +**Step 3 : Uploading it to our Galaxy server** +If your zip file is less than 2Gb, you get use the Get Data tool to upload it. +Otherwise if your zip file is larger than 2Gb, please refer to the HOWTO on workflow4metabolomics.org (http://application.sb-roscoff.fr/download/w4m/howto/galaxy_upload_up_2Go.pdf). +For more informations, don't hesitate to send us an email at supportATworkflow4metabolomics.org). + +**Advices for converting your files for the XCMS input** + +.. class:: warningmark + +VERY IMPORTANT: your data must be in **centroid** mode. In addition, we recommend you to convert your raw files to mzXML. + +We recommend the following parameters: + +Use Filtering: **True** +Use Peak Picking: **True** +Peak Peaking -Apply to MS Levels: **All Levels (1-)** : Centroid Mode +Use zlib: **64** +Binary Encoding: **64** +m/z Encoding: **64** +Intensity Encoding: **64** + +---------- +Parameters +---------- + +Maximum deviation between centroids during band detection; in ppm (default = 5) + | m/z tolerance of centroids corresponding to the same ion from one scan to the other. + | + +Accuracy of the mass spectrometer to be used during feature alignment; in ppm (default = 5) + | Should be inferior or equal to the deviation parameter above. + | + +Minimum fraction of samples in which a peak should be detected in at least one class to be kept during feature alignment (default = 0.5) + | Identical to the corresponding parameter in XCMS. + | + +Number of neighbour features to be used for imputation (default = 5) + | Select 0 to skip the imputation step. + | + + +------------ +Output files +------------ + +dataMatrix.tabular + | **dataMatrix** tabular separated file with the variables as rows and samples as columns. Missing values are indicated as 'NA' (i.e. when the signal was not significantly different from noise). + | + +sampleMetadata.tabular + | **sampleMetadata** tabular separated file containing the sample metadata as columns. + | + +variableMetadata.tabular + | **variableMetadata** tabular separated file containing the variable metadata as columns. The **timeShifted** flag is set to 1 when the flowgram is time shifted compared to the sample peak (probably due to liquid retention in the FI tube). The **corSampPeakMean** metric is the correlation between the feature flowgram and the sample peak (values are in [-1, 1]). A value below 0.2 suggests that the feature signal is affected by a strong matrix effect. The **meanSolvent** is the mean baseline signal in the feature flowgrams. The **signalOverSolventPvalueMean** is the mean p-value of the tests discriminating between signal and baseline solvent. + | + +figure.pdf + | Visualization and diagnostics about the preprocessed data set; **Feature quality**: Number of detected features per sample for each of the three categories: 'Well-behaved' features have a peak shape close to the sample peak (optimal FIA acquisition is achieved when the majority of the features fall into this category); 'Shifted' indicates a time shift compared to the sample peak, and probably results from retention in the FI tube; 'Significant Matrix Effect' corresponds to a correlation between the feature and the samples peaks of less than 0.2, which is usually caused by a strong matrix effect; **Sample peaks**: Visualization of the peak model for each sample; should have close shapes in case of similar FIA conditions; **m/z density**: may allow to detect a missing m/z value, and in turn, suggest that the *ppm* parameter should be modified; **PCA score plot** of the log10 intensities to detect sample outliers. + | + +information.txt + | Text file with all messages and warnings generated during the computation. + | + +--------------------------------------------------- + +--------------- +Working example +--------------- + +Figure output +============= + +.. image:: profia_workingExampleImage.png + :width: 600 + +--------------------------------------------------- + +---- +NEWS +---- + +CHANGES IN VERSION 3.0.0 +======================== + +NEW FEATURE + +Creation of the tool + +</help> + +<citations> + <citation type="bibtex">@Article{DelabriereSubmitted, + Title = {proFIA: A data preprocessing workflow for Flow Injection Analysis coupled to High-Resolution Mass Spectrometry}, + Author = {Delabriere, Alexis and Hohenester, Ulli and Junot, Christophe and Thevenot, Etienne A}, + Journal = {submitted}, + Year = {submitted}, + Pages = {--}, + Volume = {}, + Doi = {} + }</citation> + <citation type="doi">10.1093/bioinformatics/btu813</citation> +</citations> + +</tool>