Protein grouping is done from a parent context and consist of
Since hEIDI 1.11.0, a new peptide/protein grouping algorithm has been implemented. This is part of a global idea which is to improve global performance in hEIDI.
Indeed, datasets become bigger and bigger (ex. VELOS), and loading all data in memory in one hEIDI session is no more possible (as we did before hEIDI 1.11.0).
The purpose is now to load the minimum information in hEIDI session, and to have algorithms that save results directly to MSIdb.
We have started to optimize the peptide/Protein grouping algorithm as it requires to load a complex object tree and so is very memory consuming. Other algorithms will be optimized progressively in further hEIDI versions.
What are the changes for the user:
Peptides from different child context or identifications - attached directly or indirectly to a context - are grouped.
Peptides must have same sequence and same calculated mass to be grouped.
Peptide grouping results in new peptides attached to the parent context and having child peptides
peptide reference (sequence, ptm), missed cleavage and calculated massare copied from the first child peptide found :
experimental mass, charge, delta mass, score, retention time and fragmentation countare copied from the best child :
child listis set as peptides with same sequence, same mass are found
matches listassociated to new peptide, matches from all child peptides are grouped using matched protein. Created match
scoreis set to the max of all child matches scores and
start and endvalue are equal to child matches start and end.
Different filters could be applied during grouping.
new matchesare created.
new matchesare created. Typically this correspond to filter protein with less than x peptides…
The filtered protein or species are not taken into account in the final grouping result, they are removed from result (unlike during protein filter ). An other difference with
protein filter operation is that filtering is done on each proteins.
But before executing the protein grouping the list of proteins to be considered is filtered using optional protein filter. This means that proteins are filtered individually and filter is not applied to protein group level. See protein group filters page.
Protein grouping consist in :
Protein grouping results in new groups of proteins and peptides, attached to the parent context. The protein group and proteins matching properties are set as follow :
You need to be carefull when grouping proteins within a tree of contexts. Let's take the following example:
Rootnode |_ Context1 |_ F085255.dat |_ F085256.dat |_ F085257.dat |_ Context2 |_ F085258.dat |_ F085259.dat
Rootnodelevel, hEIDI will then group proteins from all the identification results, or
Context2), then ending with the
At present, when launching the protein group algorithm, you can tell hEIDI to filter some proteins and/or peptides. For example, if you decide to filter proteins with a number of peptides lower than 2, it is important to understand that doing this may give different results in cases 1 & 2.
Rootnode |_ Context1 ProtA (pep1, pep2) |_ Context2 ProtA (pep1, pep5)
In case 2, ProtA will be filtered at an early stage (when grouping proteins in
Context2), and will not appear in the final result.
But in case 1, when grouping proteins at the
Rootnode level, ProtA will 'gain' one peptide more (ProtA will be identified by 3 peptides instead of 2). So, ProtA will not be filtered and will appear in the final result.