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Peptide Identification from MS

Peptide identification from mass-spectra

Identify peptides by matching mass-spectra to a candidate protein database. It supports a combination of multiple search engines and allows for the creation of a decoy database, re-scoring and confidence estimation (i.e. a false discovery rate).
It includes examples for how to potentially visualize and export the results.

Per-input-file processing workflow for spectrum identification Caution:3D View only works for 3 activatedsearch engines This workflow performs a simple peptide identification from mass-spectrometry experiments (in mzML format). It can use multiple search engines to match peptides from a database tofragment spectra in your data. It combines the results, rescores them and calculates confidence values based on "decoy" entries in the database. Exports and visualizations are alsoshown. For more information see the workflow metadata. Find it here: View -> Description If using own data, you can configure the nodesand set the path. Example data is stored in theworkflow data path and referenced already. Configure and set a path where you wantto store the output. If needed, appenddecoy proteinsProtein DB as fastaSpectra as mzMLWrite to non-temporaryfolder on diskRescoring withPercolator or IDPEPPerforms ConsensusIDif multiple search engines were chosenPSM-level FDR filteringbefore exportRuns peptidesearch engine(s)export to tableread table in KNIME Append decoydatabase Agreement scatterwith table Prepareconsensus plot Prepareconsensus plot Parallel Coords 3D scatter Input File Input File File Cells to Port Output File PSM Rescoring Consensus ID FDR Filtering Search EngineCombination MzTabExporter MzTabReader Per-input-file processing workflow for spectrum identification Caution:3D View only works for 3 activatedsearch engines This workflow performs a simple peptide identification from mass-spectrometry experiments (in mzML format). It can use multiple search engines to match peptides from a database tofragment spectra in your data. It combines the results, rescores them and calculates confidence values based on "decoy" entries in the database. Exports and visualizations are alsoshown. For more information see the workflow metadata. Find it here: View -> Description If using own data, you can configure the nodesand set the path. Example data is stored in theworkflow data path and referenced already. Configure and set a path where you wantto store the output. If needed, appenddecoy proteinsProtein DB as fastaSpectra as mzMLWrite to non-temporaryfolder on diskRescoring withPercolator or IDPEPPerforms ConsensusIDif multiple search engines were chosenPSM-level FDR filteringbefore exportRuns peptidesearch engine(s)export to tableread table in KNIME Append decoydatabase Agreement scatterwith table Prepareconsensus plot Prepareconsensus plot Parallel Coords 3D scatter Input File Input File File Cells to Port Output File PSM Rescoring Consensus ID FDR Filtering Search EngineCombination MzTabExporter MzTabReader

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