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1 <tool id="chemfp_nxn_clustering" name="NxN Clustering" version="0.1">
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2 <description>of molecular fingerprints</description>
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3 <requirements>
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4 <requirement type="package" version="1.7.0">numpy</requirement>
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5 <requirement type="package" version="1.1p1">chemfp</requirement>
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6 <requirement type="package" version="1.2.1">matplotlib</requirement>
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7 <requirement type="package" version="0.12">scipy</requirement>
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8 </requirements>
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9 <command interpreter='python'>
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10 nxn_clustering.py
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11 -i $infile
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12 -t $threshold
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13 -o $outfile
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14 --oformat $oformat
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15 </command>
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16 <inputs>
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17 <param name="infile" type="data" format="fps" label="Finperprint dataset" help="Dataset missing? See TIP below"/>
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18 <param name='threshold' type='float' value='0.0' />
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19
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20 <param name='oformat' type='select' format='text' label="Format of the resulting picture">
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21 <option value='png'>PNG</option>
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22 <option value='svg'>SVG</option>
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23 </param>
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24 </inputs>
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25 <outputs>
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26 <data type="data" format="svg" name="outfile" />
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27 </outputs>
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28 <tests>
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29 <test>
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30 <param name="infile" ftype="fps" value="q.fps" />
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31 <param value='0.75' />
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32 <output ftype="svg" name="outfile" file='NxN_Clustering_on_q.svg' />
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33 </test>
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34 </tests>
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35 <help>
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36
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37 **Note**. You need molecular fingerprints in FPS format. Open Babel Fastsearch index is not supported.
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38
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39 **Note**. That tools is only useful for very small datasets.
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40
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41
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42 **What it does**
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43 Generating hierarchical clusters and visualizing clusters with dendrograms.
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44
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45 -----
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46
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47 **Example**
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48
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49 * input::
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50
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51 - fingerprints in FPS format
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52
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53 #FPS1
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54 #num_bits=881
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55 #type=CACTVS-E_SCREEN/1.0 extended=2
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56 #software=CACTVS/unknown
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57 #source=/home/mohammed/galaxy-central/database/files/000/dataset_423.dat
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58 #date=2012-02-09T13:20:37
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59 07ce04000000000000000000000000000080060000000c000000000000001a800f0000780008100000701487e960cc0bed3248000580644626004101b4844805901b041c2e
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60 19511e45039b8b2926101609401b13e40800000000000100200000040080000010000002000000000000 55169009
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61 07ce04000000000000000000000000000080060000000c000000000000001a800f0000780008100000701087e960cc0bed3248000580644626004101b4844805901b041c2e
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62 19111e45039b8b2926105609401313e40800000000000100200000040080000010000002000000000000 55079807
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63 ........
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64
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65 - Tanimoto threshold : 0.8 (between 0 and 1)
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66
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67 * output::
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68
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69 plot for the clustring
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70
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71 .. image:: ./static/images/chemfpclustoutput.svg
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72
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73
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74 </help>
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75
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76 </tool>
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