Journal of Proteome ResearchBioinformaticsPeer-reviewed journal article
Isobaric matching between runs and novel PSM-level normalization in MaxQuant strongly improve reporter ion-based quantification
Abstract
Isobaric labeling has the promise of combining high sample multiplexing with precise quantification. However, normalization issues and the missing value problem of complete n-plexes hamper quantification across more than one n-plex. Here we introduce two novel algorithms implemented in MaxQuant that substantially improve the data analysis with multiple n-plexes. First, isobaric matching between runs (IMBR) makes use of the three-dimensional MS1 features to transfer identifications from identified to unidentified MS/MS spectra between LC-MS runs in order to utilize reporter ion intensities in unidentified spectra for quantification. On typical datasets, we observe a significant gain in quantifiable n-plexes. Second, we introduce a novel PSM-level normalization, applicable to data with and without common reference channel. It is a weighted median-based method, in which the weights reflect the number of ions that were used for fragmentation. On a typical dataset, we observe complete removal of batch effects and dominance of the biological sample grouping after normalization. Furthermore, we provide many novel processing and normalization options in Perseus, the companion software for the downstream analysis of quantitative proteomics results. All novel tools and algorithms are available with the regular MaxQuant and Perseus releases, which are downloadable at http://maxquant.org.
- Citations
- 82
- FWCI
- 4.58
- Field percentile
- top 3%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Isobaric labeling update in MaxQuant
Daniela Ferretti, Pelagia Kyriakidou, … J. Cox·Journal of Proteome ResearchPeer-reviewed·Feb 25, 2025
- Systematic Evaluation of Normalization Approaches in Tandem Mass Tag and Label-Free Protein Quantification Data Using PRONE
Lis Arend, Klaudia Adamowicz, … Tanja Laske·Briefings in BioinformaticsPeer-reviewed·Apr 21, 2025
- Direct Measurement of Synchronous Precursor Selection (SPS) Accuracy in Public Proteomics Datasets
Conor Jenkins, Aimee Rinas, Benjamin C. Orsburn·bioRxiv·May 24, 2019
- Improved LC-MS chromatographic alignment increases the accuracy of label-free quantitative proteomics: Comparison of spectral counting versus ion intensity-based proteomic quantification strategies.
Daniel Ng, Jonathan D. Humphries, … Martin James Humphries·bioRxiv·Feb 24, 2017
- Accurate label-free quantification by directLFQ to compare unlimited numbers of proteomes
Constantin Ammar, Julia Patricia Schessner, … Matthias Mann·Molecular & Cellular ProteomicsPeer-reviewed·May 22, 2023
- IonQuant enables accurate and sensitive label-free quantification with FDR-controlled match-between-runs
Fengchao Yu, Sarah E. Haynes, Alexey I. Nesvizhskii·Molecular & Cellular ProteomicsPeer-reviewed·Jan 1, 2021