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In this use case, we will work with two biological replicates (named “Replicate1” and “Replicate2”).
Each sample is aliquoted in three parts: each of them is prepared using a different separation protocol (“Ultrafiltration”, “Proteominer” and “TCA Precipitation”).
Each aliquote is then deposed onto a SDS-Page gel.
When separating is done, each interesting gel band is extracted and analysed using HPLC-MSMS+Mascot+IRMa. Each band will result in one identification file (“F093496.dat”). So, the analysis of a given replicate will generate many identification files.
...Project ABC ...Replicate1 .Ultrafiltration .F093496.dat .F093497.dat ... .Proteominer ... .TCA Precipitation ... ...Replicate2 .Ultrafiltration ... .Proteominer ... .TCA Precipitation ...
Please follow the steps in the getting start to setup the MSI db connection (Mass Spectrometer Identification database), create an hEIDI project and open a working session on the MSI db.
verifier les paramètres de filtres des identification (how to view ident properties + .. view filter )
How to check filter parameters used in idenitification results
Now you need to build a context hierarchy and dispatch your identification results to map the project structure described in the first section.
See the following links to know what is a context and how to create a context hierarchy.
Protein grouping is the next step. Execute the protein grouping algorithm for all the User contexts in a specific order.
If everything has worked correctly, all the context names are now in red.
You may want to compare results from the same preparation protocol in the two replicates.
a deplacer
How to compare contexts each other.
See the following link to understand what is context comparison.
You may want to compare protocols each other for a given replicate to find the “best” one.
a deplacer
See the following link to understand what is context comparison.