CHIMERYS

CHIMERYS unifies proteomic data analysis by deconvoluting chimeric spectra through accurate predictions of peptide retention time, fragment ion intensities, and regularized linear regression to explain fragment ion intensity with minimal peptides while maintaining rigorous false discovery rate control.

Key Features:

• Chimeric Spectrum Deconvolution: CHIMERYS explains as much fragment ion intensity as possible with as few peptides as possible using regularized linear regression.
• Peptide Property Prediction: The algorithm predicts peptide retention time and fragment ion intensities to support spectrum interpretation.
• Unified Data Analysis: CHIMERYS analyzes data-dependent, data-independent, and parallel reaction monitoring experiments with a single spectrum-centric approach.
• Multiple Peptide Identification: The method accurately identifies and quantifies multiple peptides per tandem mass spectrum.
• Error Control: Rigorous false discovery rate control is applied to peptide identification results.

Scientific Applications:

• Bottom-Up Proteomics: CHIMERYS analyzes complex peptide mixtures generated by liquid chromatography-tandem mass spectrometry workflows.
• Data-Dependent Acquisition: The algorithm identifies and quantifies peptides from standard shotgun proteomics experiments.
• Data-Independent Acquisition: CHIMERYS processes spectra from DIA experiments without requiring separate software packages.
• Parallel Reaction Monitoring: The tool supports targeted proteomics data analysis within the same unified framework.

Methodology:

CHIMERYS uses a spectrum-centric search algorithm with regularized linear regression, peptide retention time prediction, and fragment ion intensity prediction to deconvolute chimeric spectra, followed by rigorous false discovery rate control for peptide identification and quantification.