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

Cox, J., Hein, M. Y., Luber, C. A., Paron, I., Nagaraj, N., & Mann, M. (2014). Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ. MOLECULAR & CELLULAR PROTEOMICS, 13(9), 2513-2526. doi:10.1074/mcp.M113.031591.

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Mol Cell Proteomics-2014-Cox-2513-26.pdf (Any fulltext), 995KB
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 Creators:
Cox, Jürgen1, Author              
Hein, Marco Y.1, Author              
Luber, Christian A.1, Author              
Paron, Igor1, Author              
Nagaraj, Nagarjuna1, Author              
Mann, Matthias1, Author              
Affiliations:
1Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              

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Free keywords: SPECTROMETRY-BASED PROTEOMICS; RESOLUTION LC-MS; MASS-SPECTROMETRY; QUANTITATIVE PROTEOMICS; BIOMARKER DISCOVERY; SHOTGUN PROTEOMICS; ANALYSIS SOFTWARE; ABSOLUTE PROTEIN; IDENTIFICATION; TISSUE
 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. For a benchmark dataset with two proteomes mixed at known ratios, we accurately detected the mixing ratio over the entire protein expression range, with greater precision for abundant proteins. The significance of individual label-free quantifications was obtained via a t test approach. For a second benchmark dataset, we accurately quantify fold changes over several orders of magnitude, a task that is challenging with label-based methods. MaxLFQ is a generic label-free quantification technology that is readily applicable to many biological questions; 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 a manageable computing time. It is implemented in the freely available MaxQuant computational proteomics platform and works completely seamlessly at the click of a button.

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Language(s): eng - English
 Dates: 2014-09
 Publication Status: Published in print
 Pages: 14
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000341785800025
DOI: 10.1074/mcp.M113.031591
 Degree: -

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Title: MOLECULAR & CELLULAR PROTEOMICS
Source Genre: Journal
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Publ. Info: 9650 ROCKVILLE PIKE, BETHESDA, MD 20814-3996 USA : AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
Pages: - Volume / Issue: 13 (9) Sequence Number: - Start / End Page: 2513 - 2526 Identifier: ISSN: 1535-9476