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openmsLFQ_​iPRG2015

Simple workflow for peptide identification and quantification.
No smart protein inference is done and all possible proteins are reported for each peptide.
Quantification is based on normalized feature intensities of peptides.

Example input data:
To download the data from the archive linked below, check the box on the folder and click on the download button (arrow) on the top left.
Download and unpack the "Example_Data" data into a directory "Example_data" right inside your KNIME workspace.

Peptide identification and quantificationSimple workflow for peptide identification and quantification.No smart protein inference is done and all possible proteins are reported for each peptide.Quantification is based on normalized feature intensities of peptides. FASTA databaseLoad picked mzML filesAnnotate features on raw mapMap IDs to annotated featuresPerform Peptide ID ZipLoopStart ZipLoopEnd File Importer File Importer FeatureFinderCentroided IDMapper MapAlignerPoseClustering FeatureLinkerUnlabeledQT ConsensusMapNormalizer IDConflictResolver FalseDiscoveryRate XTandemAdapter File Exporter Peptide identification and quantificationSimple workflow for peptide identification and quantification.No smart protein inference is done and all possible proteins are reported for each peptide.Quantification is based on normalized feature intensities of peptides. FASTA databaseLoad picked mzML filesAnnotate features on raw mapMap IDs to annotated featuresPerform Peptide ID ZipLoopStart ZipLoopEnd File Importer File Importer FeatureFinderCentroided IDMapper MapAlignerPoseClustering FeatureLinkerUnlabeledQT ConsensusMapNormalizer IDConflictResolver FalseDiscoveryRate XTandemAdapter File Exporter

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