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date Thu, 09 Aug 2018 04:25:40 -0400
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<tool id="asca" name="ASCA" version="1.0.0">
  <description>Splitting of the total variance into independent blocks according to the experimental factors and multivariate analysis (SCA) of each block</description>
  
  <!-- <requirements> -->
    <!-- <requirement type="package" version="1.1_4">r-batch</requirement> -->
<!-- %    <requirement type="package" version="1.0">r-MetStaT</requirement> -->
    <!-- <requirement type="package" version="1.70.0">bioconductor-pcamethods</requirement> -->
  <!-- </requirements> -->

  <stdio>
    <exit_code range="1:" level="fatal" />
  </stdio>
  
  <command><![CDATA[
  Rscript $__tool_directory__/asca_wrapper.R
  dataMatrix_in "$dataMatrix_in"
  sampleMetadata_in "$sampleMetadata_in"
  variableMetadata_in "$variableMetadata_in"
  factor1 "$factor1"
  factor2 "$factor2"
  scaling "$scaling"
  nPerm "$nPerm"
  threshold "$threshold"


  sampleMetadata_out "$sampleMetadata_out"
  variableMetadata_out "$variableMetadata_out"
  figure "$figure"
  information "$information"
  ]]></command>    
  
  <inputs>
    <param name="dataMatrix_in" type="data" label="Data matrix file" help="" format="tabular" />
    <param name="sampleMetadata_in" type="data" label="Sample metadata file" help="" format="tabular" />
    <param name="variableMetadata_in" type="data" label="Variable metadata file" help="" format="tabular" />
    <param name="factor1" label="Name of the sampleMetadata column containing the 1st factor for A-SCA" type="text" value="none" help=""/>
    <param name="factor2" label="Name of the sampleMetadata column containing the 2nd factor for A-SCA" type="text" value="none" help=""/>
    <param name="scaling" label="Scaling to apply to dataMatrix" type="select" help="">
	  <option value="none" selected="true">None</option>
      <option value="pareto">pareto</option>
      <option value="uv">uv</option>
	</param>
	<param name="nPerm" label="Number of permutation to perform to compute factor significance" type="select" help="">
	  <option value="100" selected="true">100</option>
      <option value="500">500</option>
      <option value="1000">1000</option>
	</param>
	<param name="threshold" type="float" value="0.05" label="Threshold for factor significance (permutation test)" help="Must be between 0 and 1"/>
  </inputs>
  
  <outputs>
    <data name="sampleMetadata_out" label="${tool.name}_${sampleMetadata_in.name}" format="tabular" ></data>
    <data name="variableMetadata_out" label="${tool.name}_${variableMetadata_in.name}" 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="dataMatrix_in" value="input-dataMatrix.tsv"/>
      <param name="sampleMetadata_in" value="input-sampleMetadata.tsv"/>
      <param name="variableMetadata_in" value="input-variableMetadata.tsv"/>
	  <param name="factor1" value="Date"/>
      <param name="factor2" value="Treatment"/>
      <param name="scaling" value="pareto"/>
      <param name="threshold" value="0.05"/>
      <param name="nPerm" value="1000"/>
	  
      <output name="asca_out" file="sampleMetadata_out.tsv" lines_diff="6"/>
    </test>
  </tests>

  
  <help>
    
.. class:: infomark
    
**Tool updates**
    
See the **NEWS** section at the bottom of this page
    
---------------------------------------------------

.. class:: infomark
    
**Authors** Marie Tremblay-Franco (W4M Core Development Team, MetaboHUB Toulouse, AXIOM) and Yann Guitton (W4M Core Development Team, Laberca, UM1329)
    
---------------------------------------------------
    
.. class:: infomark

**References**
| R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (http://www.r-project.org)
| Tim Dorscheidt (2013). MetStaT: Statistical metabolomics tools. R package version 1.0. https://CRAN.R-project.org/package=MetStaT
|
    
============
A-SCA
============
    
-----------
Description
-----------
    
| ASCA splits variance into independent blocks according to the experimental factors and performs multivariate analysis (SCA) of each block
|

-----------------
Workflow position
-----------------
    
.. image:: images/asca_workflowPositionImage.png
        :width: 600

    
-----------
Input files
-----------
 
+----------------------------+---------+
| Parameter : num + label    |  Format |
+============================+=========+
| 1 : Data matrix file       | tabular |
+----------------------------+---------+
| 2 : Sample metadata file   | tabular |
+----------------------------+---------+
| 3 : Variable metadata file | tabular |
+----------------------------+---------+


| The **required formats** for the dataMatrix, sampleMetadata, and variableMetadata files are described in the **HowTo** entitled 'Format Data For Postprocessing' available on the main page of Workflow4Metabolomics.org (http://web11.sb-roscoff.fr/download/w4m/howto/w4m_HowToFormatDataForPostprocessing_v02.pdf)


----------
Parameters
----------
	  
Data matrix file
	| variable x sample **dataMatrix** tabular separated file of the numeric data matrix, with . as decimal, and NA for missing values; the table must not contain metadata apart from row and column names; the row and column names must be identical to the rownames of the sample and variable metadata, respectively (see below)
	|

Sample metadata file
	| sample x metadata **sampleMetadata** tabular separated file of the numeric and/or character sample metadata, with . as decimal and NA for missing values
	|
	
Variable metadata file
	| variable x metadata **variableMetadata** tabular separated file of the numeric and/or character variable metadata, with . as decimal and NA for missing values
	|

Factor1
	| Name of the sampleMetadata column containing the 1st factor for A-SCA
	|

Factor2
	| Name of the sampleMetadata column containing the 2nd factor for A-SCA
	|

Scaling (default = none)
	| Mean-centering followed either by pareto scaling (**pareto**), or unit-variance scaling (**UV**)
	| 

Permutation testing for A-SCA parameters: Number of permutations (default = 100)
	| Number of random permutation on the results from ASCA. Calculate by repeating the ASCA analysis many times with permutated samples.
	| 	
	
Threshold
	| p-value significance threshold for permutation test
	|

------------
Output files
------------

sampleMetadata_out.tabular
	| sampleMetadata data file; may be identical to the input sampleMetadata in case no renaming of sample names nor re-ordering of samples (see the 'information' file for the presence/absence of modifications)
	|

variableMetadata_out.tabular
	| variableMetadata data file; may be identical to the input variableMetadata in case no renaming of variable names nor re-ordering of variables (see the 'information' file for the presence/absence of modifications)
	|

figure.pdf
	| Scree and score plots for significant parameter(s)
	| 

information.txt
	| Text file with all messages when error(s) in formats are detected
	|
    
---------------------------------------------------

---------------
Working example
---------------

.. class:: infomark

	| Data used in the following example comes from the Biosystems Data Analysis Group. They ayre included in the ASCA software(http://www.bdagroup.nl/content/Downloads/software/software.php).
	| Two features were measured on 12 individuals, using a two factor-experimental design. The 1st factor has 2 levels and the 2nd factor has 3 levels.
	| 

Input files
-----------
+---------------------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+
| Datamatrix          |   Ind1   | Ind2     | Ind3     | Ind4     | Ind5     | Ind6     | Ind7     | Ind8     | Ind9     | Ind10    | Ind11    | Ind12    |
+=====================+==========+==========+==========+==========+==========+==========+==========+==========+==========+==========+==========+==========+
| V1                  |   1.00   | 3.00     | 2.00     | 1.00     | 2.00     | 2.00     | 4.00     | 6.00     | 5.00     | 5.00     | 6.00     | 5.00     |
+---------------------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+
| V2                  |   0.60   | 0.40     | 0.70     | 0.80     | 0.01     | 0.80     | 1.00     | 2.00     | 0.90     | 1.00     | 2.00     | 0.70     |
+---------------------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+

---------------------------------------------------

+--------------------+----------+----------+
| sampleMetadata     |    F1    |    F2    |
+====================+==========+==========+
| Ind1               |    1     |    1     |
+--------------------+----------+----------+
| Ind2               |    1     |    1     |
+--------------------+----------+----------+
| Ind3               |    1     |    2     |
+--------------------+----------+----------+
| Ind4               |    1     |    2     |
+--------------------+----------+----------+
| Ind5               |    1     |    3     |
+--------------------+----------+----------+
| Ind6               |    1     |    3     |
+--------------------+----------+----------+
| Ind7               |    2     |    1     |
+--------------------+----------+----------+
| Ind8               |    2     |    1     |
+--------------------+----------+----------+
| Ind9               |    2     |    2     |
+--------------------+----------+----------+
| Ind10              |    2     |    2     |
+--------------------+----------+----------+
| Ind11              |    2     |    3     |
+--------------------+----------+----------+
| Ind11              |    2     |    3     |
+--------------------+----------+----------+

---------------------------------------------------

+--------------------+----------+
|  Variablemetadata  |  Number  |
+====================+==========+
| V1                 |    1     |
+--------------------+----------+
| V2                 |    2     |
+--------------------+----------+

---------------------------------------------------

Parameters
----------
	| Name of the sampleMetadata column containing the 1st factor for A-SCA: F1
	| Name of the sampleMetadata column containing the 2nd factor for A-SCA: F2
	| Scaling to apply to dataMatrix: none
	| Number of permutation to perform to compute factor significance: 500
	| Threshold for factor significance (permutation test): 0.05
	| 

Output files
------------
    | **1) Example of a ASCA_BDAGroup_ASCA_samplemetadata.tsv: tsv file** including PC1 and PC2 scores from F1 PCA, F2 PCA and F1xF2 PCA 


	
+--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+
| sampleMetadata     |    F1    |    F2    | F1_XSCOR-p1 | F1_XSCOR-p2 | F2_XSCOR-p1 | F2_XSCOR-p2 | Interact_XSCOR-p1 | Interact_XSCOR-p1 |
+====================+==========+==========+=============+=============+=============+=============+===================+===================+
| Ind1               |    1     |    1     | -2.66136390 | 0.307505352 | 0.986520075 | -0.25138715 | -0.31885686       | -0.77109078       |
+--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+
| Ind2               |    1     |    1     | -0.74779084 | -0.30750535 | -0.99758505 | 0.070057773 | 0.719240017       | 0.950058502       |
+--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+
| Ind3               |    1     |    2     | -1.22618411 | -0.15375267 | -0.24288670 | 0.124191016 | -0.00883820       | 0.465391498       |
+--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+

  

    | **2) Example of a ASCA_BDAGroup_ASCA_variablemetadata.tsv: tsv file** including PC1 and PC2 loadings from F1 PCA, F2 PCA and F1xF2 PCA 

	
+--------------------+----------+-------------+-------------+-------------+-------------+-------------------+--------------------+
|  variableMetadata  |  Number  | F1_XLOAD-p1 | F1_XLOAD-p2 | F2_XLOAD-p1 | F2_XLOAD-p2 | Interact_XLOAD-p1 | Interact_XLOAD-p1  |
+====================+==========+=============+=============+=============+=============+===================+====================+
| V1                 |    1     | 0.977759467 | -0.20972940 | -0.99814337 | 0.060908126 | 0.428703939       | 0.903445035        |
+--------------------+----------+-------------+-------------+-------------+-------------+-------------------+--------------------+
| V2                 |    2     | 0.977759467 | -0.30750535 | -0.06090812 | -0.99814337 | -0.90344503       | 0.428703939        |
+--------------------+----------+-------------+-------------+-------------+-------------+-------------------+--------------------+



    | **3) Example of a ASCA_information.txt: txt file** including % of explained variance and p-value of permutation test 


+----------------------+-------------------------+---------------------+
| ASCA_information.txt | % of explained variance | Permutation p-value |
+======================+=========================+=====================+
| F1                   | 81.71                   | 0.004               |
+----------------------+-------------------------+---------------------+
| F2                   | 1.29                    | 0.880               |
+----------------------+-------------------------+---------------------+
| Interaction          | 1.33                    | 0.962               |
+----------------------+-------------------------+---------------------+
| Residuals            | 15.67                   | -                   |
+----------------------+-------------------------+---------------------+


	| **4) Example of ASCA_figure.pdf: pdf file** including Scree, Score plot and barplot of leverage values only for significant factor(s)/interaction**
	| Leverage: importance of a variable in the PCA model (Nueda et al. 2007)
	
	
.. image:: BDAGroup_ASCA_figure.tif
        :width: 600

----
NEWS
----

   
</help>
  
  <citations>
    <citation type="doi">10.1093/bioinformatics/bti476</citation>
    <citation type="doi">10.1002/cem.952</citation>
    <citation type="doi">10.1093/bioinformatics/btm251</citation>
  </citations>
  
</tool>