Mercurial > repos > recetox > retip_train
comparison macros.xml @ 0:baa7c8768036 draft
"planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/retip commit 931ccc430a2b20eebd174d29b45bf3fa18e85f58"
| author | recetox |
|---|---|
| date | Wed, 30 Sep 2020 09:57:12 +0000 |
| parents | |
| children | 6462a0ac9c29 |
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| -1:000000000000 | 0:baa7c8768036 |
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| 1 <macros> | |
| 2 <token name="@TOOL_VERSION@">0.5.4</token> | |
| 3 <xml name="requirements"> | |
| 4 <requirements> | |
| 5 <container type="docker">recetox/retip:@TOOL_VERSION@-recetox0</container> | |
| 6 </requirements> | |
| 7 </xml> | |
| 8 <xml name="citations"> | |
| 9 <citations> | |
| 10 <citation type="doi">https://doi.org/10.1021/acs.analchem.9b05765</citation> | |
| 11 </citations> | |
| 12 </xml> | |
| 13 <token name="@HELP@"><![CDATA[ | |
| 14 Retip is an R package for predicting Retention Time (RT) for small molecules in a high pressure liquid | |
| 15 chromatography (HPLC) Mass Spectrometry analysis. Retention time calculation can be useful in identifying | |
| 16 unknowns and removing false positive annotations. It uses five different machine learning algorithms to built a | |
| 17 stable, accurate and fast RT prediction model: | |
| 18 | |
| 19 - Random Forest: a decision tree algorithms | |
| 20 - BRNN: Bayesian Regularized Neural Network | |
| 21 - XGBoost: an extreme Gradient Boosting for tree algorithms | |
| 22 - lightGBM: a gradient boosting framework that uses tree based learning algorithms. | |
| 23 - Keras: a high-level neural networks API for Tensorflow | |
| 24 | |
| 25 Retip also includes useful biochemical databases like: BMDB, ChEBI, DrugBank, ECMDB, FooDB, HMDB, KNApSAcK, | |
| 26 PlantCyc, SMPDB, T3DB, UNPD, YMDB and STOFF. | |
| 27 | |
| 28 **Get started** | |
| 29 | |
| 30 To use Retip, a user needs to prepare a compound retention time library. The input file | |
| 31 needs compound Name, InChiKey, SMILES code and experimental retention time information for each compound. | |
| 32 The input must be a CSV file. Retip will use this input file to build a the model and will predict | |
| 33 retention times for other biochemical databases or an input query list of compounds. It is suggested that | |
| 34 the file has at least 300 compounds to build a good retention time prediction model. | |
| 35 ]]> | |
| 36 </token> | |
| 37 </macros> |