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Metabolomics (Accurate Mass Search only)

Untargeted Metabolomics through accurate mass search in MS data

This workflow performs a simple untargeted identification and quantification of metabolites from liquid chromatography mass spectrometry experiments (in mzML format).
It uses an accurate mass search based on feature data to lookup compounds in a database. Exports and visualizations of quant. results are also shown.
Input data is automatically downloaded via http from a public respository.


Load mzML Mass trace extraction Retention time correction and linkingbetween samples Sample-wise adduct grouping This workflow performs a simple untargeted identification and quantification of metabolites from liquid chromatography massspectrometry experiments (in mzML format). It uses an accurate mass search based on feature data to lookup compounds in a database. Exports and visualizations are also shown. For more information see the workflow metadata. Find it here: View -> Description 1) (Down)loading input filesIn case you have own data, reconfigure or replace with"Input Files"node for local files. 5) Mapping compounds from a table to the found featuresFiles provided for the default dataset within the workflow.Adapt them for your own usage in the workflow "data" folder 2) Annotate input data with conditionsAnnotate the files to specify to which condition theybelong. Note: Fractions are not supported yet. Please runthe workflow per fraction, then.In the second node, choose which comparison to analyzefor the fold changes. Note: The evaluation of missing compounds is only recommended for small in-housedatabases or benchmark datasets where the majority of compounds are to be found.The result is a potentially large table of pictures. 6a) Choose which comparison to analyze for the foldchanges and plots. You can later go back and chooseanother comparison. The expensive spectrum processingwon't need to be executed again. 3) Feature finding and adduct decharging 4) Alignment and linking 6b) Calculate fold changesand errors Visualizations Report convex hullsUse adductinformationfor alignmentUse adductinformationfor linkingConsider H, Na, KNow also considerNH4 andneutral water lossList files to downloadfrom the serverConnect to serverLoad custom/benchmark metabolites databaseas tableMapping databaseentries to found featureslist of pos. adducts(incl. in workflow data)Here: Just H+, Na+, K+list of neg. adducts(incl. in workflow data)Here: unusedto KNIME tableWrite kroenik format fileof missing features forinspection in external viewer(TOPPView) ZipLoopStart ZipLoopEnd FeatureFinderMetabo FileConverter MapAlignerPoseClustering FeatureLinkerUnlabeledQT MetaboliteAdductDecharger MetaboliteAdductDecharger Table Creator HTTP(S) Connector CSV Reader AccurateMassSearch Input File Input File MzTabReader Download from HTTPS Table View withPubChem Browser CSV Writer Construct featuresnot found Create AMS inputfiles from table Convert ret.time to seconds Calculate missingmetabolites Find closest match toexpected compounds Choose comparison Compute fold change Visualize errorsas violins Annotate fileswith conditions Create table of pictures atplaces with missing compounds Massage table Load mzML Mass trace extraction Retention time correction and linkingbetween samples Sample-wise adduct grouping This workflow performs a simple untargeted identification and quantification of metabolites from liquid chromatography massspectrometry experiments (in mzML format). It uses an accurate mass search based on feature data to lookup compounds in a database. Exports and visualizations are also shown. For more information see the workflow metadata. Find it here: View -> Description 1) (Down)loading input filesIn case you have own data, reconfigure or replace with"Input Files"node for local files. 5) Mapping compounds from a table to the found featuresFiles provided for the default dataset within the workflow.Adapt them for your own usage in the workflow "data" folder 2) Annotate input data with conditionsAnnotate the files to specify to which condition theybelong. Note: Fractions are not supported yet. Please runthe workflow per fraction, then.In the second node, choose which comparison to analyzefor the fold changes. Note: The evaluation of missing compounds is only recommended for small in-housedatabases or benchmark datasets where the majority of compounds are to be found.The result is a potentially large table of pictures. 6a) Choose which comparison to analyze for the foldchanges and plots. You can later go back and chooseanother comparison. The expensive spectrum processingwon't need to be executed again. 3) Feature finding and adduct decharging 4) Alignment and linking 6b) Calculate fold changesand errors Visualizations Report convex hullsUse adductinformationfor alignmentUse adductinformationfor linkingConsider H, Na, KNow also considerNH4 andneutral water lossList files to downloadfrom the serverConnect to serverLoad custom/benchmark metabolites databaseas tableMapping databaseentries to found featureslist of pos. adducts(incl. in workflow data)Here: Just H+, Na+, K+list of neg. adducts(incl. in workflow data)Here: unusedto KNIME tableWrite kroenik format fileof missing features forinspection in external viewer(TOPPView) ZipLoopStart ZipLoopEnd FeatureFinderMetabo FileConverter MapAlignerPoseClustering FeatureLinkerUnlabeledQT MetaboliteAdductDecharger MetaboliteAdductDecharger Table Creator HTTP(S) Connector CSV Reader AccurateMassSearch Input File Input File MzTabReader Download from HTTPS Table View withPubChem Browser CSV Writer Construct featuresnot found Create AMS inputfiles from table Convert ret.time to seconds Calculate missingmetabolites Find closest match toexpected compounds Choose comparison Compute fold change Visualize errorsas violins Annotate fileswith conditions Create table of pictures atplaces with missing compounds Massage table

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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On NodePit since: 2022-05-21
Last update: 2026-01-19
Created with KNIME version: v4.4.1
Tags: MetabolomicsOpenMSmass spectrometry

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