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How to Identify Low-Abundance Modified Peptides with Proteomics Mass Spectrometry

Our White Paper explains the solid analytic methodology behind SorcererScore™. We believe SorcererScore uniquely enables deep proteomics by presenting peptide IDs close to their raw data from using simple-to-understand analytics. Its foundation is based on well-established components, namely the cross-correlation search engine (John Yates Lab, Scripps), target-decoy search (Steve Gygi Lab, Harvard), and a rigorous peptide-to-protein framework (Ruedi Aebersold Lab, ETH Zurich).

Unlike opaque software that report peptide IDs not readily verifiable, SorcererScore respects the integrity of the science by being transparent and hypothesis-driven, and by presenting data-driven evidence that can be drilled down to any level by scientists.