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South africa metabolomics (#243)
* rough update of doc * finish new lfq workflow descriptions * update tutorial before workshop * Update main.yml * remove plaintext * fix layout * adjust fdr node changes --------- Co-authored-by: Samuel Wein <[email protected]>
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docs/tutorials/knime-user-tutorial/lfq-peptide-protein.md

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@@ -29,7 +29,7 @@ different concentrations. [^1]
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started. In order to specify the database, [select](https://abibuilder.cs.uni-tuebingen.de/archive/openms/Tutorials/Example_Data/Labelfree/databases/s_pyo_sf370_potato_human_target_decoy_with_contaminants.fasta) {path}`Example_Data,Labelfree,databases,/break,s_pyo_sf370_potato_human_target_decoy_with_contaminants.fasta`
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- Connect the **out** port of the `CometAdapter` to `ZipLoopEnd` and we have a very basic peptide identification workflow.
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## ```{note}
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```{note}
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You might also want to save your new identification workflow under a different name. Have a look at <a href="#duplicating-workflows">duplicating workflows</a>
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for information on how to create copies of workflows.
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```
@@ -92,7 +92,7 @@ FDR of < 1 %.
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**Community Nodes** > **OpenMS** > **Identification Processing**). `FalseDiscoveryRate` is meant to be run on data with protein inferencences
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(more on that later), in order to just use it for peptides, open the configure window, select "show advanced parameter" and toggle "force" to true.
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- In order to set the FDR level to 1%, we need an `IDFilter` node from **Community Nodes** > **OpenMS** > **Identification Processing**.
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Configuring its parameter `FDR→PSM` to 0.01 will do the trick. The FDR calculations (embedded in the idXML) from
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Configuring the parameter `FDR→PSM` of the `FalseDiscoveryRate` node to 0.01 will do the trick. The FDR calculations (embedded in the idXML) from
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the `FalseDiscoveryRate` node will go into the *in* port of the `IDFilter` node.
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- Execute your workflow and inspect the results using `IDTextReader` like you did before. How many peptides did you
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identify at this FDR threshold?

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