title: RockerBox: analysis and filtering of massive proteomics search results.
abstract: A major problem in the analysis of mass spectrometry-based proteomics data is the vast growth of data volume, caused by improvements in sequencing speed of mass spectrometers. This growth affects analysis times and storage requirements so severely that many analysis tools are no longer able to cope with the increased file sizes. We present a tool, RockerBox, to address size problems for search results obtained from the widely used Mascot search engine. RockerBox allows for a fast evaluation of large result files by means of a number of commonly accepted metrics that can often be viewed through charts. Moreover, result files can be filtered without altering their informative content, based on a number of FDR calculation methods. File sizes can be reduced dramatically, often to a tenth of their original size, thus relaxing the need for storage and computation power, and boosting analysis of current and future proteomics experiments.
authors.affiliation: Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands.
authors.forename: Henk W P
authors.initials: HW
authors.lastname: van den Toorn
authors.forename: Javier
authors.initials: J
authors.lastname: Muñoz
authors.forename: Shabaz
authors.initials: S
authors.lastname: Mohammed
authors.forename: Reinout
authors.initials: R
authors.lastname: Raijmakers
authors.forename: Albert J R
authors.initials: AJ
authors.lastname: Heck
authors.forename: Bas
authors.initials: B
authors.lastname: van Breukelen
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D057809:HEK293 Cells; D006801:Humans; D013058:Mass Spectrometry / Q000295:instrumentation / Q000379:methods*; D040901:Proteomics / Q000379:methods*; D012372:ROC Curve; D012984:Software