HyperQuantA Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics

Quantitative proteomics has evolved
considerably over the last
decade with the advent of higher order multiplexing (HOM) techniques.
With the development of methods such asmultitagging, cPILOT,
hyperplexing, BONPlex, and MITNCAT, the HOM technique is rapidly taking
the center stage in multiplexed quantitative proteomics. These studies
combined MS1 and MS2 labels in a single experiment
enabling higher sample throughput. While HOM is highly promising,
the computational analysis is still a big challenge, as the available
tools cannot harness its power completely. We have developed a new
quantitative pipeline, HyperQuant to aid in accurately quantitating
complex HOM data. The pipeline uses identification results from either
MaxQuant or any other search engine and quantitation results from
QuantWizIQ. The Mapper and Combiner modules of HyperQuant
allow facile integration of the labeled data, along with peptide spectrum
match (PSM) intensity/ratio integration for proteins, respectively,
for each PSM label combination. This also includes appropriate combination
of replicates/fractions before summarizing the protein intensity/ratio,
leading to robust quantitation. To the best of our knowledge, this
is the first tool for the quantitation of HOM data with flexibility
for any combination of MS1 and MS2 labels. We
demonstrate its utility in analyzing two 18-plex data sets from the
hyperplexing and the BONplex studies. The tool is open source and
freely available for noncommercial use. HyperQuant is a highly valuable
tool that will help in advancing the field of multiplexed quantitative
proteomics.