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author | marie-tremblay-metatoul |
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date | Fri, 21 Sep 2018 05:51:14 -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="choo_datamatrix.txt"/> <param name="sampleMetadata_in" value="choo_samplemetadata.txt"/> <param name="variableMetadata_in" value="choo_variablemetadata.txt"/> <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="sampleMetadata_out" file="ASCA_choo_samplemetadata.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>