Mercurial > repos > bgruening > chemfp
view nxn_clustering.xml @ 42:0a1c281e9224 draft default tip
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/chemicaltoolbox/chemfp commit 7fb96a3844b4771084f18de2346ed6d5e241d839"
author | bgruening |
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date | Sat, 25 Sep 2021 19:05:59 +0000 |
parents | 07e1a9d090e4 |
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<tool id="ctb_chemfp_nxn_clustering" name="NxN clustering" version="@TOOL_VERSION@+@VERSION_SUFFIX@"> <description>of molecular fingerprints</description> <macros> <token name="@TOOL_VERSION@">1.6.1</token> <token name="@VERSION_SUFFIX@">0</token> </macros> <requirements> <requirement type="package" version="@TOOL_VERSION@">chemfp</requirement> <requirement type="package" version="2.2.5">matplotlib</requirement> <requirement type="package" version="1.2.1">scipy</requirement> </requirements> <command detect_errors="exit_code"> <![CDATA[ python '$__tool_directory__/nxn_clustering.py' -i '$infile' -t $threshold #if str($output_files) in ['both', 'image']: --cluster '$image' #end if #if str($output_files) in ['both', 'matrix']: --smatrix '$similarity_matrix' #end if --oformat '$oformat' ]]> </command> <inputs> <param name="infile" type="data" format="fps" label="Fingerprint dataset" help="Dataset missing? See TIP below"/> <param name='threshold' label='Threshold' type='float' value='0.0' /> <param name='oformat' type='select' format='text' label="Format of the resulting picture"> <option value='png'>PNG</option> <option value='svg'>SVG</option> </param> <param name='output_files' type='select' format='text' label="Output options"> <option value='both'>NxN matrix and image</option> <option value='image'>Image</option> <option value='matrix'>NxN ḿatrix</option> </param> </inputs> <outputs> <data name="image" format="svg" label="${tool.name} on ${on_string} - Dendrogram Image"> <filter>output_files == "both" or output_files == "image"</filter> <change_format> <when input="oformat" value="png" format="png"/> </change_format> </data> <data name="similarity_matrix" format="txt" label="${tool.name} on ${on_string} - Similarity Matrix"> <filter>output_files == "both" or output_files == "matrix"</filter> </data> </outputs> <tests> <test> <param name="infile" ftype="fps" value="targets.fps" /> <param name='threshold' value='0.75' /> <param name='oformat' value='svg' /> <param name='output_files' value='both' /> <output name="similarity_matrix" file='NxN_Clustering_on_q.txt' ftype="txt"/> <output name="image" ftype="svg"> <assert_contents> <has_text text="L 49.515625 72.90625" /> <has_text text="Q 48 40.375 41.703125 38.8125" /> </assert_contents> </output> </test> </tests> <help> <![CDATA[ .. class:: infomark **What this tool does** Based on a set of fingerprints, generates a square self-similarity (NxN) matrix, as well as a dendrogram visualizing the clusters derived from it using hierarchical clustering. For the clustering and the fingerprint handling the chemfp_ project is used. .. _chemfp: http://chemfp.com/ ----- .. class:: warningmark **Hint** The plotting of the dendrogram is sensible only with a small dataset - if more than around 20 fingerprints are used the plot will be unreadable. ----- .. class:: infomark **Input** Molecular fingerprints in FPS format. Open Babel Fastsearch index is not supported. * Example:: - fingerprints in FPS format #FPS1 #num_bits=881 #type=CACTVS-E_SCREEN/1.0 extended=2 #software=CACTVS/unknown #source=/home/mohammed/galaxy-central/database/files/000/dataset_423.dat #date=2012-02-09T13:20:37 07ce04000000000000000000000000000080060000000c000000000000001a800f0000780008100000701487e960cc0bed3248000580644626004101b4844805901b041c2e 19511e45039b8b2926101609401b13e40800000000000100200000040080000010000002000000000000 55169009 07ce04000000000000000000000000000080060000000c000000000000001a800f0000780008100000701087e960cc0bed3248000580644626004101b4844805901b041c2e 19111e45039b8b2926105609401313e40800000000000100200000040080000010000002000000000000 55079807 ........ - Tanimoto threshold : 0.8 (between 0 and 1) ----- .. class:: informark **Output** * Example:: .. image:: $PATH_TO_IMAGES/NxN_clustering.png ]]> </help> <citations> <citation type="doi">10.1186/1758-2946-5-S1-P36</citation> </citations> </tool>