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MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra
journal contribution
posted on 2015-12-17, 04:16 authored by Viktoria Dorfer, Peter Pichler, Thomas Stranzl, Johannes Stadlmann, Thomas Taus, Stephan Winkler, Karl MechtlerToday’s
highly accurate spectra provided by modern tandem
mass spectrometers offer considerable advantages for the analysis
of proteomic samples of increased complexity. Among other factors,
the quantity of reliably identified peptides is considerably influenced
by the peptide identification algorithm. While most widely used search
engines were developed when high-resolution mass spectrometry data
were not readily available for fragment ion masses, we have designed
a scoring algorithm particularly suitable for high mass accuracy.
Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and
CID fragmentation type data. The algorithm confidently explains more
spectra at the same false discovery rate than Mascot or SEQUEST on
examined high mass accuracy data sets, with excellent overlap and
identical peptide sequence identification for most spectra also explained
by Mascot or SEQUEST. MS Amanda, available at http://ms.imp.ac.at/?goto=msamanda, is provided free of charge both as standalone version for integration
into custom workflows and as a plugin for the Proteome Discoverer
platform.