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Elsevier, Molecular and Cellular Proteomics, 9(13), p. 2513-2526, 2014

DOI: 10.1074/mcp.m113.031591

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Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We developed a new intensity determination and normalization procedure called MaxLFQ that is fully compatible with any peptide or protein separation prior to LC-MS analysis. Protein abundance profiles are assembled using the maximum possible information from MS-signals given that the presence of quantifiable peptides varies from sample to sample. On a benchmark dataset with two proteomes mixed at known ratios, we accurately detect the mixing ratio over the entire protein expression range, with higher precision for abundant proteins. The significance of individual label-free quantifications is obtained by a t-test approach. On a second benchmark dataset, we accurately quantify fold changes over several orders of magnitudes, a task that is challenging with label-based methods. MaxLFQ is a generic label-free quantification technology that is readily applicable to tackle many biological questions and it is compatible with standard statistical analysis workflows, and it has been validated in many and diverse biological projects. Our algorithms can handle very large experiments of 500+ samples in manageable computing time. It is implemented in the freely-available MaxQuant computational proteomics platform and works completely seamlessly at the click of a button (www.maxquant.org).