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determine_bc.xml
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<tool id="Determine_BC" name="Determine_batch_correction" version="3.0.0">
<description>to choose between linear, lowess and loess methods</description>
<macros>
<import>macros.xml</import>
</macros>
<requirements>
<requirement type="package" version="1.1_4">r-batch</requirement>
<requirement type="package" version="1.7_8">r-ade4</requirement>
<requirement type="package" version="1.70.0">bioconductor-pcamethods</requirement>
</requirements>
<stdio>
<exit_code range="1:" level="fatal" />
</stdio>
<command><![CDATA[
Rscript $__tool_directory__/batch_correction_3Lwrapper.R
analyse "determine_bc"
sampleMetadata "$sampleMetadata"
dataMatrix "$dataMatrix"
ref_factor "$ref_factor"
#if str($advance.option ) == 'show':
span $advance.span
#else:
span "none"
#end if
out_graph_pdf "$out_graph_pdf"
out_preNormSummary "$out_preNormSummary"
@SM_CUSTOM@
]]></command>
<inputs>
<param name="dataMatrix" type="data" label="Data matrix file " help="" format="tabular" />
<param name="sampleMetadata" type="data" label="Sample metadata file " help="must contain at least the three following columns: 'batch' + 'injectionOrder' + 'sampleType'" format="tabular" />
<expand macro="sm_customisation"/>
<expand macro="foi"/>
<conditional name="advance">
<param name="option" type="select" label="Advanced options" help="should only be put at 'show' if you have good understanding of the span parameter and are willing to adjust it">
<option value="show">show</option>
<option value="hide" selected="true">hide</option>
</param>
<when value="show">
<param name="span" type="float" value="0.85" label="span" help="applied to lowess and loess regression"/>
</when>
<when value="hide"/>
</conditional>
</inputs>
<outputs>
<data name="out_graph_pdf" label="Determine_BC_graph" format="pdf" ></data>
<data name="out_preNormSummary" label="Determine_BC_preNormSummary" format="tabular" ></data>
</outputs>
<tests>
<test>
<param name="dataMatrix" value="input-determinebc-dataMatrix.tsv"/>
<param name="sampleMetadata" value="input-determinebc-sampleMetadata.tsv"/>
<param name="ref_factor" value="batch"/>
<param name="option" value="hide"/>
<param name="span" value="none"/>
<output name="out_preNormSummary" file="output-determinebc-preNormSummary.txt"/>
</test>
</tests>
<help>
.. class:: infomark
**Authors**
| Jean-Francois Martin - PF MetaToul-AXIOM ; INRAE ; MetaboHUB (for original version of this tool and overall development of the R script)
.. class:: infomark
**Contributors**
| Melanie Petera - PFEM ; INRAE ; MetaboHUB (for R wrapper and R script improvement)
.. class:: infomark
**Wrapping**
| Marion Landi - FLAME ; PFEM (for original xml interface and R wrapper)
| Franck Giacomoni - PFEM ; INRAE ; MetaboHUB (for original xml interface and R wrapper)
---------------------------------------------------
.. class:: infomark
**Please cite** If you use this tool, please cite:
| `F.M. van der Kloet, I. Bobeldijk, E.R. Verheij, R.H. Jellema. (2009). "Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping." Journal of Proteome Research p5132-5141 <http://www.ncbi.nlm.nih.gov/pubmed/19754161>`_
---------------------------------------------------
==========================
Determine_batch_correction
==========================
|
-----------
Description
-----------
|
Generates outputs to help to determine what type of regression to use between linear or non-linear (lowess or loess) functions for batch correction
using quality control pooled samples (QC-pools) with correction algorithm as described by Van Der Kloet (J Prot Res 2009).
Warning: this module does *not* deliver which choice should be made in model type;
it only provides information to help users in determining which choice may be appropriate, based on their own expertise.
This tool is meant to be used prior to the Batch_correction tool to help to make a choice in parameters,
but it is not a requirement and thus can be avoided.
|
-----------------
Workflow position
-----------------
.. image:: determine_batch_correction.png
:width: 600
-----------
Input files
-----------
+--------------------------+-----------+
| Parameter : num + label | Format |
+==========================+===========+
| 1 : Data matrix file | tabular |
+--------------------------+-----------+
| 2 : Sample metadata file | tabular |
+--------------------------+-----------+
|
The data matrix file must contain the intensity values of variables.
| First line must contain all the samples' names.
| First column must contain all the variables' ID.
The sample metadata file must contain at least the three following columns:
| - a batch column (default to "*batch*") to identify the batches of analyses
| - an injection order column (default to "*injectionOrder*") composed of integers defining the injection order of samples
| - a sample type column (default to "*sampleType*") indicating if a sample is a biological one ("*sample*"), a QC-pool ("*pool*") or a blank ("*blank*")
| *Default values* can be changed according to your data coding using the customisation parameters in the "**Sample metadata file coding parameters**" section.
**Notes concerning your design:**
| - the 3 mandatory columns must not contain NA
| - your data should contain at least 3 QC-pools in each batch for intra-batch **linear** adjustment and 8 for **lo(w)ess** adjustment
----------
Parameters
----------
Sample metadata file coding parameters
| Enables to give the names of columns in the sample metadata table that contain the injection order, the batches and the sample types.
| Also enables to specify the sample type coding used in the sampletype column.
|
Factor of interest
| Name of the factor (column header) that will be used as a categorical variable for design plots (often a biological factor ; if none, put the batch column name).
| This factor does not affect correction calculation.
|
Advanced options
| Should only be put at "show" if you have good understanding of the span parameter and are willing to adjust it.
|
Span
| - When advanced option is at "hide" (default):
| default is 1 for loess regression and is two times the ratio between number of pools and number of samples for lowess regression.
| - When advanced option is at "show":
| filled value is used for lowess and loess regressions.
------------
Output files
------------
Determine_BC_preNormSummary.tabular
| tabular output
| Meaning of results of diagnosis analysis
| 0 - no preliminary-condition problem
| 1 - standard deviation of QC-pools or samples = 0
| 2 - insufficient number of QC-pools within a batch (n=3 for linear, n=8 for lowess or loess)
| 2.5 - less than 2 samples within a batch
| 3 - significant difference between QC-pools' and samples' means
| 4 - denominator =0 when on 1 pool per batch non-zero
| 5 - (linear regression only) the slopes ratio “QC-pools/samples” is lower than -0.2
| 6 - (linear regression only) none of the pool or sample could be corrected if negative and infinite values are turned into NA
|
Determine_BC_graph.pdf
| graphical output
| One page per ion. Plots regression curves for all methods allowed and plot.design results regarding the factor of interest.
---------------------------------------------------
----------------------
Additional information
----------------------
.. class:: warningmark
Refer to the corresponding "W4M HowTo" page:
| `MS data processing - Filters and normalisation <https://download.workflow4metabolomics.org/docs/w4e2018/2018-10_EC_W4E%20-%20Dataprocessing_Filter_and_normalisation.pdf>`_
|
|
</help>
<!-- [RECOMMANDED] All citations associated to this tool (main citation given above and other references). Can be extracted from the history panel -->
<citations>
<!-- [HELP] As DOI or BibTex entry -->
<citation type="doi">10.1021/pr900499r</citation>
</citations>
</tool>