HyperQuant

HyperQuant integrates identification and quantitation results to process higher order multiplexing (HOM) quantitative proteomics data from techniques such as multitagging, cPILOT, hyperplexing, BONPlex, and MITNCAT.

Key Features:

• Integration of identification and quantitation results: Integrates identification outputs from search engines such as MaxQuant with QuantWiz^IQ quantitation to combine peptide/protein identifications and quantitative measurements.
• Mapper and Combiner modules: Uses Mapper and Combiner modules to integrate labeled data with peptide-spectrum-match (PSM) intensity and ratio information across PSM label combinations.
• Replicate and fraction combination: Combines replicates and fractions prior to protein-level summarization of intensities and ratios.
• Label flexibility: Handles any combination of MS^1 and MS^2 labels to support diverse HOM experimental designs.

Scientific Applications:

• Hyperplexing analysis: Processes hyperplexing datasets, including high-plex experiments such as 18-plex, for quantitative proteomics.
• BONplex and related HOM workflows: Analyzes BONplex datasets and other HOM workflows including multitagging, cPILOT, and MITNCAT.
• Proteomics research: Enables biomarker discovery, pathway analysis, and systems biology studies through integrated HOM quantitation.

Methodology:

Integrates identification results (e.g., MaxQuant or other search engines) with QuantWiz^IQ quantitation, applies Mapper and Combiner modules to merge labeled PSM intensity/ratio data across label combinations, combines replicates and fractions, and summarizes protein intensities and ratios.