ProDBWiki/DeveloperDocumentation/reduceSearches

Reduce Searches

Idea

To get good results with a mascot search, you choose many different search parameters. For example more than one database, 0 - 5 or more missed cleavage sites, a wide spectra for the peptide tolerance and small steps (50-100ppm in 10ppm steps). With every parameter more, the number of searches increases. Rapidly you have 100 or more searches for one scan. And if you want to analyse more than one scan, you can wait very long for your results.

If you choose the Reduce Searches, you can decrease the number of searches. This function tries which parameters give the best results and minimizes the searches. At first it only iterates over the missed cleavage sites and saves the best one. Then it iterates over the peptide tolerance (the missed cleavage site is always the best one) and saves the best combination from missed cleavage site and peptide tolerance. For all other searches these parameters are used and only the remaining parameters are iterated. By the use of this tool, you can reduce the number of searches to less than 10.

How to use

To use this feature select the field Reduce Searches from the dropdown menu Search for mixture. All other parameters can be chosen as normal. Click on Search to submit the search. After all searches are finished, you can click on Results to get the results. Be aware that not all searches are generated only a few with the best parameters (so you can see only the results for these).

What Did I Do

I add two functions to msanalysis.cgi: create_searchp_reduce and reduce_searches. Both functions are called from msanalysis.cgi, after checking if Reduce Searches was selected in the search from. The first function create_searchp_reduce sorts the searchParameters in a special way, so that they can be used for the second function reduce_searches. All searchParams are stored in the hash %sortSearchDB, this hash has the different selected databases as keys and is returned. %sortSearchDB contains hashes (%sortSearchP) which have the different peptide tolerances as keys. If the key from %sortSearchDB is database A, the hash %sortSearchP contains only search parameters with database A as attribute. %sortSearchP also contains hashes (%sortSearchC) which have different missed cleavage site as keys. %sortSearchC contains only an array (@sortC) with all search parameters with the same database (key from %sortSearchDB), same peptide tolerance (key from %sortSearchP) and same missed cleavage site (key from %sortSearchC). The search parameters are sorted in the order: DB -> PeptidToleranz -> MissedCleavageSites. For example: You have database DB A and DB B, peptidetolerance 50, 75, 100ppm and missed cleavage sites 0, 1, 2 and different fixed and variable modifications. Than you get the following hash %sortSearchDB:

              Key    contains      Key  contains      Key  contains   contains
sortSearchDB: DB A   sortSearchP:  50   sortSearchC:  1    @sortC:    SP with:
                                                      2    @sortC:    SP with:
                                                      3    @sortC:    SP with:

                                   75   sortSearchC:  1    @sortC:    SP with:
                                                      2    @sortC:    SP with:
                                                      3    @sortC:    SP with:

                                   100  sortSearchC:  1    @sortC:    SP with:
                                                      2    @sortC:    SP with:
                                                      3    @sortC:    SP with:

              DB B   sortSearchP:  50   sortSearchC:  1    @sortC:    SP with:
                                                      2    @sortC:    SP with:
                                                      3    @sortC:    SP with:

                                   75   sortSearchC:  1    @sortC:    SP with:
                                                      2    @sortC:    SP with:
                                                      3    @sortC:    SP with:

                                   100  sortSearchC:  1    @sortC:    SP with:
                                                      2    @sortC:    SP with:
                                                      3    @sortC:    SP with:

Author: Nicole de la Chaux