diff modulated_modularity_clustering.xml @ 1:2e7d47c0b027 draft

"planemo upload for repository https://malex@toolshed.g2.bx.psu.edu/repos/malex/secimtools"
author malex
date Mon, 08 Mar 2021 22:04:06 +0000
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children caba07f41453
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+++ b/modulated_modularity_clustering.xml	Mon Mar 08 22:04:06 2021 +0000
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+<tool id="secimtools_modulated_modularity_clustering" name="Modulated Modularity Clustering (MMC)"  version="@WRAPPER_VERSION@">
+    <description>with visual summaries.</description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="requirements" />
+    <command detect_errors="exit_code"><![CDATA[
+modulated_modularity_clustering.py
+--input $input
+--design $design
+--ID $uniqID
+--out $output
+--figure $figure
+--sigmaLow $sigmaLow
+--sigmaHigh $sigmaHigh
+--sigmaNum $sigmaNum
+--correlation $corr
+    ]]></command>
+    <inputs>
+        <param name="input" type="data" format="tabular" label="Wide Dataset" help="Input your tab-separated wide format dataset. If not tab separated see TIP below." />
+        <param name="design" type="data" format="tabular" label="Design Dataset" help="Input your design file (tab-separated). Note you need a 'sampleID' column. If not tab separated see TIP below."/>
+        <param name="uniqID" type="text" size="30" label="Unique Feature ID" help="Name of the column in your wide dataset that has unique identifiers.." />
+        <param name="sigmaLow" type="float" size="6" value="0.05" label="Lower sigma bound" help="Default: 0.05." />
+        <param name="sigmaHigh" type="float" size="6" value="0.50" label="Upper sigma bound" help="Default: 0.50." />
+        <param name="sigmaNum" type="float" size="6" value="451" label="Number of Sigma values" help="Number of values of sigma to search. Default: 451." />
+        <param name="corr" type="select" value="pearson" label="Correlation method" help="Select correlation method for preliminary correlation before clustering. Default: Pearson." >
+            <option value="pearson" selected="true">Pearson</option>
+            <option value="kendall" selected="true">Kendall</option>
+            <option value="spearman" selected="true">Spearman</option>
+        </param>
+    </inputs>
+    <outputs>
+        <data format="tabular" name="output" label="${tool.name} on ${on_string}: Values"/>
+        <data format="pdf" name="figure" label="${tool.name} on ${on_string}: Heatmaps"/>
+    </outputs>
+    <tests>
+        <test>
+            <param name="input"   value="ST000006_data.tsv"/>
+            <param name="design"  value="ST000006_design.tsv"/>
+            <param name="uniqID"  value="Retention_Index" />
+            <param name="corr"    value="pearson" />
+            <output name="output" file="ST000006_modulated_modularity_clustering_out.tsv" compare="sim_size" delta="10000"/>
+            <output name="figure" file="ST000006_modulated_modularity_clustering_figure.pdf" compare="sim_size" delta="10000" />
+        </test>
+    </tests>
+    <help><![CDATA[
+
+@TIP_AND_WARNING@
+
+**Tool Description**
+
+Modulated Modularity Clustering method (MMC) was designed to detect latent structure in data using weighted graphs.
+The method searches for optimal community structure and detects the magnitude of pairwise relationships.
+The optimal number of clusters and the optimal cluster size are selected by the method during the analysis.
+
+The initial boundaries (lower and upper) for sigma as well as the number of points in the search grid (number of sigma values) are specified initially by the user.
+The boundaries are extended automatically by the algorithm if the values are close to the boundary. The correlation type (Pearson, Kendall or Spearman) can be specified.
+
+More details about the method can be found in:
+
+Stone, E. A., and Ayroles, J. F. (2009). Modulated modularity clustering as an exploratory tool for functional genomic inference. PLoS Genet, 5(5), e1000479.
+
+
+--------------------------------------------------------------------------------
+
+**Input**
+
+    - Two input datasets are required.
+
+@WIDE@
+
+**NOTE:** The sample IDs must match the sample IDs in the Design File (below). Extra columns will automatically be ignored.
+
+@METADATA@
+
+@UNIQID@
+
+**Lower sigma value**
+
+    - Default: 0.05.
+
+**Upper sigma value**
+
+    - Default: 0.50.
+
+**Sigma values**
+
+    - Number of values of sigma to search. Default: 451.  Higher numbers increase the precision but decrease the performance time.
+
+**Correlation method**
+
+    - Correlation method for preliminary correlation before clustering. Default = Pearson.
+
+--------------------------------------------------------------------------------
+
+**Output**
+
+The tool produces four files: a single TSV file and three PDF files:
+
+(1) a TSV file containing the algorithm summaries and
+(2) three PDF files containing (i) unsorted, (ii) sorted, and (iii) sorted and smoothed dependency heatmaps produced by the MMC algorithm respectively.
+
+
+    ]]></help>
+    <expand macro="citations"/>
+</tool>