Mercurial > repos > bgruening > biomodels_biomd0000001066
annotate biomodels_BIOMD0000001066.xml @ 4:48024c5a155f draft default tip
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit db3b6bfca3b7fbacd3e6e907a138b0c83ba8443a
author | bgruening |
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date | Wed, 20 Mar 2024 16:58:56 +0000 |
parents | e5d28e255f58 |
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rev | line source |
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4
48024c5a155f
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit db3b6bfca3b7fbacd3e6e907a138b0c83ba8443a
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1 <tool id="biomodels_biomd0000001066" name="Random Forest model" version="@VERSION@" profile="@PROFILE@"> |
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1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
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2 <description>to predict efficacy of immune checkpoint blockade across multiple cancer patient cohorts</description> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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parents:
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3 <macros> |
4
48024c5a155f
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit db3b6bfca3b7fbacd3e6e907a138b0c83ba8443a
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parents:
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4 <import>macros.xml</import> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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5 </macros> |
4
48024c5a155f
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit db3b6bfca3b7fbacd3e6e907a138b0c83ba8443a
bgruening
parents:
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6 <expand macro="creators" /> |
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1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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7 <requirements> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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8 <container type="docker">quay.io/galaxy/biomodels_biomd0000001066:@VERSION@</container> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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9 </requirements> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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10 <command><![CDATA[ |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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11 cp /home/\$NB_USER/forest16.onnx ./ && |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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12 python '$biom_script' |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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13 ]]> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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14 </command> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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15 <configfiles> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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16 <configfile name="biom_script"> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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17 <![CDATA[ |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
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18 import os |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
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19 import argparse |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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20 import numpy |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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21 import onnxruntime as rt |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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22 import pandas as pd |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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23 |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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24 #if $input_file.ext == "xlsx": |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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25 data_test = pd.read_excel('$input_file') |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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26 #elif $input_file.ext == "tabular": |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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27 data_test = pd.read_csv('$input_file', sep="\t") |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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28 #elif $input_file.ext == "csv": |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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29 data_test = pd.read_csv('$input_file', sep=",") |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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30 #end if |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
parents:
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31 |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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32 rf16=["Cancer_Type2", "Albumin", "HED", "TMB", "FCNA", "BMI", "NLR", "Platelets", "HGB", "Stage (1:IV; 0:I-III)", "Age", "Drug (1:Combo; 0:PD1/PDL1orCTLA4)", "Chemo_before_IO (1:Yes; 0:No)","HLA_LOH", "MSI (1:Unstable; 0:Stable_Indeterminate)", "Sex (1:Male; 0:Female)"] |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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33 x_test16 = pd.DataFrame(data_test, columns=rf16) |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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34 sess = rt.InferenceSession(os.getcwd() + "/forest16.onnx") |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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35 input_name = sess.get_inputs()[0].name |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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36 label_name = sess.get_outputs()[0].name |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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37 pred_onx = sess.run([label_name], {input_name: x_test16.astype(numpy.float32).values})[0] |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
bgruening
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38 x_test16["Predictions"] = pred_onx |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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parents:
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39 x_test16.to_csv('$output_file', sep="\t", index=None) |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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40 |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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41 ]]> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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parents:
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42 </configfile> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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parents:
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43 </configfiles> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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44 <inputs> |
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45 <param name="input_file" type="data" label="Test data" format="tabular,csv,xlsx" multiple="false" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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46 </inputs> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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47 <outputs> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit fe5cbcff4786c445b47538472ca4b4a099d2f652
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48 <data format="tabular" name="output_file" label="Predicted data"></data> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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49 </outputs> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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50 <tests> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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51 <test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit fe5cbcff4786c445b47538472ca4b4a099d2f652
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52 <param name="input_file" value="test_data.tabular" ftype="tabular" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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53 <output name="output_file" file="pred_data.tabular"> |
1748c5d74df5
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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54 <assert_contents> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit fe5cbcff4786c445b47538472ca4b4a099d2f652
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55 <has_n_columns n="17" /> |
e5d28e255f58
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit fe5cbcff4786c445b47538472ca4b4a099d2f652
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56 <has_n_lines n="296" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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57 </assert_contents> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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58 </output> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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59 </test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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60 <test> |
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61 <param name="input_file" value="test_data.csv" ftype="csv" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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62 <output name="output_file" file="pred_data.tabular"> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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63 <assert_contents> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit fe5cbcff4786c445b47538472ca4b4a099d2f652
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64 <has_n_columns n="17" /> |
e5d28e255f58
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit fe5cbcff4786c445b47538472ca4b4a099d2f652
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65 <has_n_lines n="296" /> |
0
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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66 </assert_contents> |
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67 </output> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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68 </test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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69 <test> |
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70 <param name="input_file" value="test_data.xlsx" ftype="xlsx" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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71 <output name="output_file" file="pred_data.tabular"> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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72 <assert_contents> |
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73 <has_n_columns n="17" /> |
e5d28e255f58
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit fe5cbcff4786c445b47538472ca4b4a099d2f652
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74 <has_n_lines n="296" /> |
0
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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75 </assert_contents> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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76 </output> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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77 </test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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78 </tests> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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79 <help> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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80 <![CDATA[ |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/biomodelsML commit cffacdd593bbb69ea96cfd89e8062b17984451e5
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81 **What it does** |
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82 |
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83 |
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84 The tool makes prediction of either responder (1) or non-responder (0) to an immunotherapy for multiple different cancer types. The features used to train a Random Forest (RF16) model include 16 genomic, molecular, demographic, and clinical. More details in associated publication: "Improved prediction of immune checkpoint blockade efficacy across multiple cancer types" (https://pubmed.ncbi.nlm.nih.gov/34725502/). The model is available via a Docker container. |
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85 |
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86 **Description** |
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87 |
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88 This is a Random Forest algorithm-based machine learning model called RF16, which incorporates a total of 16 genomic, molecular, demographic, and clinical features to predict the immunotherapy response for a patient. The model assigns a value of 0 for NonResponder and 1 for Responder. Please be aware that the column names in the GitHub code and the downloaded dataset from the publication may vary. Users are advised to make minor adjustments to either the code or the dataset to ensure compatibility. The curated version of the model has modified the column names in the training code to align with the dataset. The features used are: "Cancer_Type2", "Albumin", "HED", "TMB", "FCNA", "BMI", "NLR", "Platelets", "HGB", "Stage (1:IV; 0:I-III)", "Age", "Drug (1:Combo; 0:PD1/PDL1orCTLA4)", "Chemo_before_IO (1:Yes; 0:No)","HLA_LOH", "MSI (1:Unstable; 0:Stable_Indeterminate)", "Sex (1:Male; 0:Female)" |
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89 |
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90 **Input file** |
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91 |
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92 Provide a tabular file (as tabular or csv or xlsx) containing all the features as mentioned above. |
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93 |
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94 **Output file** |
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95 |
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96 Returns predicted data as a tabular file - the predictions are concatenated as a last column of the test data. |
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97 |
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98 ]]> |
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99 </help> |
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100 <citations> |
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101 <citation type="bibtex"> |
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102 @ARTICLE{BIOMD0000001066, |
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103 Author = {Chowell D and et al.}, |
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104 title = {{Chowell2022 - Random Forest model to predict efficacy of immune checkpoint blockade across multiple cancer patient cohorts}}, |
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105 url = {https://www.ebi.ac.uk/biomodels/BIOMD0000001066} |
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106 } |
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107 </citation> |
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108 </citations> |
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109 </tool> |