mzRecal

mzRecal recalibrates peptide mass measurements from mass spectrometry-based proteomic datasets to improve peptide identification, alignment, and quantitation across diverse mass analyzers.

Key Features:

• Universal Compatibility: Supports automatic recalibration of datasets derived from common types of mass analyzers.
• Standard Open Formats: Utilizes standard open formats for input and output to facilitate integration with existing data processing pipelines.
• Physical Principles-Based Approach: Implements recalibration grounded in physical principles to achieve high accuracy in mass measurements.
• Implementation Language: Implemented in the Go programming language.

Scientific Applications:

• Peptide Identification: Improves accuracy of peptide identification by refining measured peptide masses.
• Feature Alignment: Enhances alignment of features across runs and instruments through consistent mass calibration.
• Quantitation: Increases reliability of quantitative proteomics by correcting systematic mass measurement errors.
• Cross-Instrument Data Quality Optimization: Optimizes data quality from diverse mass analyzers to support downstream proteomic analyses.

Methodology:

Uses identified peptides from tandem mass spectrometry (MS/MS) to automatically recalibrate datasets and correct systematic mass measurement errors.