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comparison PhageDPO.xml @ 33:269e43aa8721 draft

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author jose_duarte
date Tue, 13 Jun 2023 09:53:02 +0000
parents 2a17d4833692
children 10b8c91f55fd
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32:5a0afb1578ea 33:269e43aa8721
11 <command detect_errors="exit_code"><![CDATA[ 11 <command detect_errors="exit_code"><![CDATA[
12 python '$__tool_directory__/DPOGALAXY.py' '$adv.model' '${input1}' 12 python '$__tool_directory__/DPOGALAXY.py' '$adv.model' '${input1}'
13 ]]></command> 13 ]]></command>
14 <inputs> 14 <inputs>
15 <param type="data" name="input1" format="fasta" label="Fasta file"/> 15 <param type="data" name="input1" format="fasta" label="Fasta file"/>
16 <section name = 'adv' title= 'Advanced Options' expanded = 'False'>
17 <param type = "select" name="model" label="Model">
18 <option value="SVM4311" selected="yes">SVM4311</option>
19 <option value="ANN7185">ANN7185</option>
20 </param>
21 </section>
22
23 </inputs> 16 </inputs>
24 <outputs> 17 <outputs>
25 <data name="output1" format="html" from_work_dir="output.html" 18 <data name="output1" format="html" from_work_dir="output.html"
26 label="DPO Prediction"/> 19 label="DPO Prediction"/>
27 </outputs> 20 </outputs>
39 ======== 32 ========
40 33
41 Predicts the existance of Phage Polysaccharide Depolymerase. 34 Predicts the existance of Phage Polysaccharide Depolymerase.
42 35
43 PhageDPO is a python script that predicts the existance of depolymerases (DPOs) using supervised machine learning models. 36 PhageDPO is a python script that predicts the existance of depolymerases (DPOs) using supervised machine learning models.
44 Two different datasets were used to develop two models: The SVM model was built using a dataset with 45 features and 4311 examples (1437 positives and 2874 negatives) and the ANN model was created using a dataset with 166 features and 7185 examples (1437 positives and 5748 negatives).
45 37
46 **Inputs:** 38 **Inputs:**
47 39
48 * fasta file: fasta file format contain the nucleotide sequences. 40 * fasta file: fasta file format contain the nucleotide sequences.
49 41
50 **Advanced options:**
51
52 * Model: selection of the model to run: the SVM model (default) or the ANN model. The SVM model focus on true positive detection while avoiding false positives. On the other hand, the ANN model uses more negative data ensuring that all DPOs are identified.
53
54 **Outputs:** 42 **Outputs:**
55 43
56 The tool outputs an html file containing the name of the sequence and the percentage of positive prediction for DPO. 44 The tool outputs an html file containing the name of the sequence and the percentage of positive prediction for DPO.
57 45
58 **Requirements:** 46 **Requirements:**
59 47
60 * Biopython 48 * Biopython
61 * Sklearn 49 * Sklearn
62 * Numpy 50 * Numpy
63 * Pandas 51 * Pandas
64 52
65 ]]></help> 53 ]]></help>
66 </tool> 54 </tool>