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author test-svm
date Wed, 08 Aug 2012 19:20:14 -0400
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1 <tool id="kmersvm_classify" name="Score Sequences of Interest">
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2 <description>using SVM weights</description>
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3 <command interpreter="python">scripts/kmersvm_classify.py -q $inputA $inputB</command>
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4 <inputs>
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5 <param format="tabular" name="inputA" type="data" label="SVM Weights"/>
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6 <param format="fasta" name="inputB" type="data" label="Test Sequences"/>
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7 </inputs>
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8 <outputs>
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9 <data format="tabular" name="kmersvm_scores.out" from_work_dir="kmersvm_scores.out" />
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10 </outputs>
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11 <tests>
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12 <test>
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13 <param name="inputA" value="test_weights.out" />
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14 <param name="inputB" value="classify_test.fa" />
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15 <output name="output" file="classify_output.out" />
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16 </test>
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17 </tests>
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18 <help>
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19
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20 **What it does**
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21
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22 Takes as input one file of weights generated by Train SVM and one FASTA file containing sequences to be predicted.
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23
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24 Returns a file containing the names of the input sequences, as well as the scores and posterior probabilities of the input sequences.
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25
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26 ----
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27
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28 **Example**
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29
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30 Scores file::
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31
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32 #seq_id posterior_prob svm_score
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33 mm8_chr1_3089935_3090035_+ 0.042414638227 -2.13990367846
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34 mm8_chr1_5031335_5031435_+ 0.351943600792 -0.478063299876
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35 mm8_chr1_5103742_5103842_+ 0.194625711202 -1.01493730026
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36 mm8_chr1_5650372_5650472_+ 0.105376843506 -1.49141463695
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37
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38 </help>
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39 </tool>