DeltaMass

DeltaMass detects and visualizes mass shifts in proteomic open-search results to identify post-translational modifications (PTMs) and chemical changes from LC-MS data.

Key Features:

• Kernel-density-based estimation: Employs a kernel-density approach to estimate observed mass shifts and resolve poorly resolved mass deltas in open-search results.
• Database mapping (UniMod): Maps detected mass shifts to known modifications using UniMod and generates additional possible chemical change annotations.
• Mass-shift peak list generation: Produces mass-shift peak lists from open-search outputs for downstream analysis.
• Mass recalibration and MS1 precursor detection: Recalibrates masses and detects precursors in MS1 signals to improve the accuracy of modification calls.
• Statistical treatment of modified peptide forms: Provides rigorous statistical analysis of modified peptide forms to extract meaningful information from complex proteomic datasets.

Scientific Applications:

• Open-search analysis: Supports open-search workflows with large precursor ion mass tolerance windows to evaluate potential sets of PTMs and chemical modifications.
• PTM and chemical modification identification: Facilitates identification of post-translational modifications and chemical changes in peptides derived from LC-MS experiments.
• Statistical characterization of mass shifts: Enables detection and characterization of poorly resolved mass deltas and unusual artifacts within proteomic datasets.
• Improving modification reliability: Enhances reliability of modification detection through mass recalibration and accurate MS1 precursor identification.

Methodology:

Uses kernel-density-based statistical estimation, maps mass shifts to UniMod and other generated chemical-change hypotheses, generates mass-shift peak lists, and performs mass recalibration with MS1 precursor detection.