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"planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/retip commit 9bc547872c98a9c13c561d15e8990fe82bdc0e72"
author recetox
date Fri, 28 Jan 2022 16:29:12 +0000
parents 63b2c4cfaa48
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211d986c6b42 "planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/retip commit 931ccc430a2b20eebd174d29b45bf3fa18e85f58"
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1 <macros>
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2 <token name="@TOOL_VERSION@">0.5.4</token>
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3
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4 <xml name="creator">
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5 <creator>
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6 <person
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7 givenName="Muhammad"
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8 familyName="Usman"
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9 url="https://github.com/smartx-usman"
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10 identifier="0000-0002-9598-0704" />
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11 <person
29aaad80929f "planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/retip commit 9bc547872c98a9c13c561d15e8990fe82bdc0e72"
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12 givenName="Aleš"
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13 familyName="Křenek"
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14 url="https://github.com/ljocha"
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15 identifier="0000-0002-3395-3196" />
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16 <organization
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17 url="https://www.recetox.muni.cz/"
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18 email="GalaxyToolsDevelopmentandDeployment@space.muni.cz"
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19 name="RECETOX MUNI" />
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20 </creator>
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21 </xml>
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0
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23 <xml name="requirements">
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24 <requirements>
6
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25 <container type="docker">recetox/retip:@TOOL_VERSION@-recetox4</container>
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26 </requirements>
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27 </xml>
211d986c6b42 "planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/retip commit 931ccc430a2b20eebd174d29b45bf3fa18e85f58"
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28 <xml name="citations">
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29 <citations>
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30 <citation type="doi">https://doi.org/10.1021/acs.analchem.9b05765</citation>
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31 </citations>
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32 </xml>
211d986c6b42 "planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/retip commit 931ccc430a2b20eebd174d29b45bf3fa18e85f58"
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33 <token name="@HELP@"><![CDATA[
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34 **Retip** is an R package for predicting Retention Time (RT) for small molecules in a high pressure liquid
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35 chromatography (HPLC) Mass Spectrometry analysis. Retention time calculation can be useful in identifying
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36 unknowns and removing false positive annotations. It uses five different machine learning algorithms to built a
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37 stable, accurate and fast RT prediction model:
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38
8
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39 - Random Forest: a decision tree algorithms
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40 - BRNN: Bayesian Regularized Neural Network
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41 - XGBoost: an extreme Gradient Boosting for tree algorithms
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42 - lightGBM: a gradient boosting framework that uses tree based learning algorithms.
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43 - Keras: a high-level neural networks API for Tensorflow
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44
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45 Retip also includes useful biochemical databases like: BMDB, ChEBI, DrugBank, ECMDB, FooDB, HMDB, KNApSAcK,
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46 PlantCyc, SMPDB, T3DB, UNPD, YMDB and STOFF.
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48 **Get started**
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50 To use Retip, a user needs to prepare a compound retention time library. The input file
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51 needs compound Name, InChiKey, SMILES code and experimental retention time information for each compound.
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52 The input must be a CSV file. Retip will use this input file to build a the model and will predict
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53 retention times for other biochemical databases or an input query list of compounds. It is suggested that
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54 the file has at least 300 compounds to build a good retention time prediction model.
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55 ]]>
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56 </token>
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57 </macros>