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‎tools/phenomenal/ms/camera/camera-annotate-peaks.cwl‎

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@@ -6,7 +6,7 @@ label: CAMERA Annotate Peaks
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hints:
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DockerRequirement:
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dockerPull: quay.io/biocontainers/bioconductor-camera
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dockerPull: container-registry.phenomenal-h2020.eu/phnmnl/camera
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SoftwareRequirement:
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packages:
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camera:
@@ -32,7 +32,7 @@ outputs:
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baseCommand: xsAnnotate.r
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arguments:
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- input=$(inputs.camera_annotate_peaks.path
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- input=$(inputs.camera_annotate_peaks.path)
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- output=output.Rdata
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doc: |

‎tools/phenomenal/ms/camera/camera-find-adducts.cwl‎

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@@ -6,7 +6,7 @@ label: CAMERA Find Adducts
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hints:
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DockerRequirement:
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dockerPull: quay.io/biocontainers/bioconductor-camera
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dockerPull: container-registry.phenomenal-h2020.eu/phnmnl/camera
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SoftwareRequirement:
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packages:
1212
camera:

‎tools/phenomenal/ms/camera/camera-find-isotopes.cwl‎

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@@ -6,7 +6,7 @@ label: CAMERA Find Isotopes
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hints:
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DockerRequirement:
9-
dockerPull: quay.io/biocontainers/bioconductor-camera
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dockerPull: container-registry.phenomenal-h2020.eu/phnmnl/camera
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SoftwareRequirement:
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packages:
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camera:

‎tools/phenomenal/ms/camera/camera-group-corr.cwl‎

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#!/usr/bin/env cwl-runner
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cwlVersion: v1.0
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class: CommandLineTool
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label: CAMERA Group Corr
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hints:
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DockerRequirement:
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dockerPull: container-registry.phenomenal-h2020.eu/phnmnl/camera
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SoftwareRequirement:
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packages:
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camera:
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specs:
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- https://bio.tools/camera
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- https://identifiers.org/rrid/RRID:SCR_002466
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inputs:
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xs_annotate:
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type: File
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format: iana:application/x-r-data
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label: xsAnnotate file
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doc: A rdata file with a xsAnnotate object from one sample
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correlation:
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type: float
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label: The correlation threshold for EIC correlation
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p_value:
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type: float
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label: The p-value threshold for testing correlation of significance
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outputs:
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grouped_peaks:
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type: File
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format: iana:application/x-r-data
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doc: |
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a rData file containing one xsAnnotate object containing grouped peaks in
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so called pseudospectra
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outputBinding:
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glob: ouput.Rdata
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baseCommand: groupCorr.r
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arguments:
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- input=$(inputs.xs_annotate.path)
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- output=output.Rdata
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- correlations=$(inputs.correlation)
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- pvalue=$(inputs.pvalue)
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doc: |
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Peak grouping after correlation information into pseudospectrum
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groups for an xsAnnotate object.
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**Please cite**:
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R Core Team (2013). R: A language and Environment for Statistical Computing. http://www.r-project.org
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**References**
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Kuhl C, Tautenhahn R, Boettcher C, Larson TR and Neumann S (2012). "CAMERA:
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an integrated strategy for compound spectra extraction and annotation of
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liquid chromatography/mass spectrometry data sets." Analytical Chemistry, 84,
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pp. 283-289. http://pubs.acs.org/doi/abs/10.1021/ac202450g.
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$namespaces:
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iana: "https://www.iana.org/assignments/media-types/"
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‎tools/phenomenal/ms/camera/camera-group-fwhm.cwl‎

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#!/usr/bin/env cwl-runner
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cwlVersion: v1.0
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class: CommandLineTool
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label: CAMERA Group FWHM
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hints:
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DockerRequirement:
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dockerPull: container-registry.phenomenal-h2020.eu/phnmnl/camera
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SoftwareRequirement:
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packages:
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camera:
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specs:
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- https://bio.tools/camera
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- https://identifiers.org/rrid/RRID:SCR_002466
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inputs:
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xs_annotate:
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type: File
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format: iana:application/x-r-data
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label: xsAnnotate file
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doc: A rdata file with a xsAnnotate object from one sample
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sigma:
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type: float
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label: The multiplier of the standard deviation
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per_fwhm:
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type: float
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label: Percentage of the width of the FWHM
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intensity_values:
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type: string
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label: Intensity values for ordering.
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doc: Allowed values are into, maxo, intb
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outputs:
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grouped_peaks:
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type: File
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format: iana:application/x-r-data
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doc: |
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a rData file containing one xsAnnotate object containing grouped peaks in
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so called pseudospectra
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outputBinding:
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glob: ouput.Rdata
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baseCommand: groupFWHM.r
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arguments:
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- input=$(inputs.xs_annotate.path)
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- output=output.Rdata
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- sigma=$(inputs.sigma)
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- perfwhm=$(inputs.per_fwhm)
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- intval=$(inputs.intensity_values)
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doc: |
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Group peaks of a xsAnnotate object according to their retention time into
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pseudospectra-groups. Uses the peak FWHMs as grouping borders.
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**Please cite**:
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R Core Team (2013). R: A language and Environment for Statistical Computing. http://www.r-project.org
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**References**
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Kuhl C, Tautenhahn R, Boettcher C, Larson TR and Neumann S (2012). "CAMERA:
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an integrated strategy for compound spectra extraction and annotation of
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liquid chromatography/mass spectrometry data sets." Analytical Chemistry, 84,
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pp. 283-289. http://pubs.acs.org/doi/abs/10.1021/ac202450g.
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$namespaces:
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iana: "https://www.iana.org/assignments/media-types/"
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‎tools/phenomenal/ms/camera/camera-prepareoutput.cwl‎

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#!/usr/bin/env cwl-runner
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cwlVersion: v1.0
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class: CommandLineTool
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label: Prepare output for doing multi/uni variate
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hints:
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DockerRequirement:
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dockerPull: container-registry.phenomenal-h2020.eu/phnmnl/camera
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SoftwareRequirement:
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packages:
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camera:
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specs:
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- https://bio.tools/camera
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- https://identifiers.org/rrid/RRID:SCR_002466
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inputs:
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camera:
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type: File
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format: iana:application/x-r-data
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label: XCMS-Set file
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doc: This is the quantification results from CAMERA.
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scores:
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type: File
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format: iana:application/text
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label: Identification results
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phenotypes:
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type: File
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format: iana:text/csv
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label: phenotype and metadata information
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doc: |
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Example of phenotype information:
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The first column of this table must show the raw data file name (for
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example sample1.mzML). The file must have a header. Other information
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can also be added to this table such as age, gender, time etc. This will
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be output as they are.
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| RawFile | Class | Groups | Type | rename | Technical repl | Age | Gender |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| Sample1.mzML | Sample | Disease | keep | Disease1 | 1 | 35 | M |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| Sample2.mzML | Sample | Disease | keep | Disease2 | 1 | 35 | M |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| Sample3.mzML | Sample | Control | keep | Control1 | 2 | 37 | F |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| Sample4.mzML | Sample | Control | keep | Control2 | 2 | 37 | F |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| Blank1.mzML | Blank | NA | remove | NA | NA | NA | NA |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| Blank2.mzML | Blank | NA | remove | NA | NA | NA | NA |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| Blank3.mzML | Blank | NA | remove | NA | NA | NA | NA |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| D1.mzML | D1 | NA | remove | NA | NA | NA | NA |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| D2.mzML | D2 | NA | remove | NA | NA | NA | NA |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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| D3.mzML | D3 | NA | remove | NA | NA | NA | NA |
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+----------------+----------+-----------+----------+------------+------------------+-------+----------+
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ppm:
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type: float
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label: PPM tolerance for matching
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doc: |
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m/z tolerance for matching identification results to quantification
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(parts per million)
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rt:
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type: float
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label: RT tolerance for matching
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doc: |
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Retention time tolerance for matching identification results to
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quantification (seconds).
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higher_the_better:
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type: string
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label: Higher the score the better?
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doc: |
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If the higher score represents a better hit. For example,
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FragmenterScore will be higher for reliable hits but q-value will be
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lower. ("true" or "false")
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score_type:
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type: string
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label: which score to use?
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doc: |
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"q.value", "Score" for the Normalized score, or "FragmenterScore"
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Depending on the previous tool used to perform the identification,
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FragmenterScore, Score and q.value can be used. q.value should only be
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selected if the MetFrag scores have been converted to posterior error
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probability score.
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impute:
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type: string
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label: Impute IDs within pc groups?
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doc: |
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"true" or "false"
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Metabolites quantification profile often result in a number signals. One
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some of this signal can be identified. If this parameter is set, the
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unidentified signals will be imputed by the identification based on
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CAMERA grouping.
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rename:
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type: string
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default: "false"
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label: Rename the sample file names to specific names
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doc: |
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"true" or "false". If "true" then the samples will be renamed based on
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information provide in column "rename_column"
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rename_column:
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type: string
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default: renameto
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label: column with the names you want to rename the samples to
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column_type:
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type: string
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default: type
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label: the name of the column showing the samples you want to keep
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doc: |
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The phenotype file must have a column showing which samples to keep and
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which to remve. Enter name of that column.
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selected_type:
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type: string
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default: sample
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label: Which type of samples to keep
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doc: |
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Based on information in "column_type" enter which sample type should be kept.
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only_report_with_id:
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type: string
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default: "false"
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label: Do you want to use the features without ID?
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doc: |
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"true" or "false". If "true" then only identified metabolites will be
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reported.
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combine_replicate:
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type: string
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default: "false"
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label: Do you want to median technial replicates?
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doc: |
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"true" or "false". If "true" then the technical replicates (duplicate
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injections) will be medianed. This information should be provided in an
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additional column in the phenotype information.
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log:
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type: string
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label: Do you want to perform log2 transformation?
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doc: '"true" or "false"'
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combine_replicate_column:
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type: string
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default: rep
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label: Column that represents the technical replicates.
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doc: The column name indicating technical replicate in the phenotype file.
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sample_coverage:
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type: float
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default: 0.0
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label: Percentage of non-missing values
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doc: How much of non-missing value should be present for each feature.
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sample_coverage_method:
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type: string
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default: global
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doc: |
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Do you want to apply coverage globally across all the runs or per group?
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For applying globally use "global" otherwise write name of the column
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showing the grouping.
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outputs:
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peaktable:
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type: File
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format: iana:text/tab-separated-values
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label: A tabular peak table containing abundances
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outputBinding:
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glob: peak_table.tsv
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variables:
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type: File
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format: iana:text/tab-separated-values
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label: Variable data containing identification.
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doc: |
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Aggregated identification results either from metfragaggregator or pep
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score generator
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outputBinding:
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glob: variables.tsv
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metadata:
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type: File
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format: iana:text/tab-separated-values
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label: Sample metadata
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outputBinding:
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glob: metadata.tsv
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baseCommand: prepareOutput.r
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arguments:
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- inputcamera=$(inputs.camera.path)
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- inputscores=$(input.scores.path)
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- inputpheno=$(input.phenotypes.path)
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- ppm=$(inputs.ppm)
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- rt=$(inputs.rt)
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- higherTheBetter=$(inputs.higher_the_better)
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- scoreColumn=$(inputs.score_type)
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- impute=$(inputs.impute)
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- typeColumn=$(inputs.column_type)
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- selectedType=$(inputs.selected_type)
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- rename=$(inputs.rename)
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- renameCol=$(inputs.rename_column)
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- onlyReportWithID=$(inputs.only_report_with_ID)
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- combineReplicate=$(inputs.combine_replicate)
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- combineReplicateColumn=$(inputs.combine_replicate_column)
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- outputPeakTable=peak_table.tsv
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- outputVariables=variables.tsv
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- outputMetaData=metadata.tsv
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- log=$(inputs.log)
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- sampleCoverage=$(inputs.sample_coverage)
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- sampleCoverageMethod=$(inputs.sample_coverage_method)
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doc: |
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Converts the quantification and identification results to tabular files for
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multivariate and univariate data analysis
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**Please cite**:
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R Core Team (2013). R: A language and Environment for Statistical Computing. http://www.r-project.org
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**References**
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Kuhl C, Tautenhahn R, Boettcher C, Larson TR and Neumann S (2012). "CAMERA:
218+
an integrated strategy for compound spectra extraction and annotation of
219+
liquid chromatography/mass spectrometry data sets." Analytical Chemistry, 84,
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pp. 283-289. http://pubs.acs.org/doi/abs/10.1021/ac202450g.
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$namespaces:
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iana: "https://www.iana.org/assignments/media-types/"
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