Turbo SLoMo: high throughput protein modification localisation
Turbo SLoMo is a modified version of SLoMo a PTM site localisation tool created at Birmingham University.
SLoMo is a software tool which can localise and score sites of protein modification in mass spectrometry data.
Turbo SLoMo has been created to allow high throughput modification site localisation using the SLoMo algorithm. Turbo SLoMo takes input from pepxml formatted mass spectrometry search results and MS/MS spectra in the MGF format. Modifications of interest can be specified via the command line along with batch options allowing large datasets to be broken down into smaller sets when using a computational cluster.
Export Search Results
SLoMo has been tested with Mascot, Sequest, and OMSSA. We use Turbo-SLoMo with mainly Mascot results.
To extract Mascot 2.4 results in the correct format first go to the Mascot results page. On this page there is an export button, use this to export the results as first a pepxml file and then as an MGF file. If you have access to you Mascot server this process can be automated using the export_dat.pl found in the Mascot cgi folder. This export_dat.pl tool can also be used to convert Mascot Percolator datp files.
Name of the pepXML file to load (ignored if –database specified)
Name of the output file to be created
Name of the omssa tab file to load (ignored if –pepxml or –database specified)
Use database <database> (created with –outdb option)
Create a database file only, do not score localisations
Save the database generated from the input file to <database> (default: temp.db)
Input MGF spectra file (default: input.mgf)
Analyse all modifications that match this pattern. E.g. -mod=phospho will process all phosphorylation modifications. Special case: “ALL” will analyse all mods if results file (default: ALL)
Fragmentation mode e.g. cid or etd (use –validmodes to see list of all modes). Modes can be specified in the Slomo.ini file. (default:ecd)
Print usage information
Print a list of valid strings to use with -mode extracted from Slomo.ini
Number of jobs to split results into
Job number to run (based on batchn number of jobs)
Maximum number of Mods in a single peptide for it to be processed. Large numbers of modifications in a single peptide can lead to massive computational overhead.
Minimum number of Mods in a single peptide for it to be processed.
If you need help or have any queries, please contact us using the details below.
James Wright (firstname.lastname@example.org)