Mercurial > repos > malex > secimtools
diff modulated_modularity_clustering.xml @ 1:2e7d47c0b027 draft
"planemo upload for repository https://malex@toolshed.g2.bx.psu.edu/repos/malex/secimtools"
author | malex |
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date | Mon, 08 Mar 2021 22:04:06 +0000 |
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children | caba07f41453 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/modulated_modularity_clustering.xml Mon Mar 08 22:04:06 2021 +0000 @@ -0,0 +1,106 @@ +<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>