Icon

basic_​peptide_​identification_​with_​inference

This workflow performs a basic peptide identification search, infers proteins and computes abundances using spectral counting.
The mzML files are searched with X!Tandem against a protein database. ProteinInference infers the proteins from peptide identifications
and ProteinQuantifier uses spectral counting to compute protein abundances.
No result files are written out. Instead the MzTabReader node allows access to a table of protein
identifications and the CSVReader node shows a table of the abundances.

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" inside your KNIME workspace.

Merge PSMs of all runs for protein inference Append files (but do no merge as ProteinQuantifierneeds to distinguis where IDs came from) Basic Peptide Identification with Protein Inference and simple QuantificationThis workflow performs a basic peptide identification search, infers proteins and computes abundances using spectral counting.The mzML files are searched with X!Tandem against a protein database. ProteinInference infers the proteins from peptide identificationsand ProteinQuantifier uses spectral counting to compute protein abundances.No result files are written out. Instead the MzTabReader node allows access to a table of proteinidentifications and the CSVReader node shows a table of the abundances. Define input data here.If the example data is used, it shouldbe in Example_Data next to thisworkflow. Right click and selectFile Tableto view table with proteinabundances Right click and selectone of the tables at thebottom to view identificationresults Node 2Node 4Node 78Node 80Node 81Node 82Node 83Node 84Node 98Node 99Node 101Node 102Node 103Spectrum Files (.mzML)Protein Database (.fasta) ZipLoopStart ZipLoopEnd XTandemAdapter IDMerger ProteinInference FalseDiscoveryRate MzTabExporter MzTabReader ProteinQuantifier IDMerger URI Port toVariable CSV Reader String to Path(Variable) File Importer File Importer Merge PSMs of all runs for protein inference Append files (but do no merge as ProteinQuantifierneeds to distinguis where IDs came from) Basic Peptide Identification with Protein Inference and simple QuantificationThis workflow performs a basic peptide identification search, infers proteins and computes abundances using spectral counting.The mzML files are searched with X!Tandem against a protein database. ProteinInference infers the proteins from peptide identificationsand ProteinQuantifier uses spectral counting to compute protein abundances.No result files are written out. Instead the MzTabReader node allows access to a table of proteinidentifications and the CSVReader node shows a table of the abundances. Define input data here.If the example data is used, it shouldbe in Example_Data next to thisworkflow. Right click and selectFile Tableto view table with proteinabundances Right click and selectone of the tables at thebottom to view identificationresults Node 2Node 4Node 78Node 80Node 81Node 82Node 83Node 84Node 98Node 99Node 101Node 102Node 103Spectrum Files (.mzML)Protein Database (.fasta)ZipLoopStart ZipLoopEnd XTandemAdapter IDMerger ProteinInference FalseDiscoveryRate MzTabExporter MzTabReader ProteinQuantifier IDMerger URI Port toVariable CSV Reader String to Path(Variable) File Importer File Importer

Nodes

Extensions

Links

Download

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

Download Workflow
Created by: walzer
Created at: 2014-08-25
On NodePit since: 2023-05-06
Last update: 2024-11-18
Created with KNIME version: v4.7.2
Tags: OpenMSMass spectrometryPeptide identificationProtein identificationDatabase searchFDRProtein Quantification

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!