Publications

MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale

Published in Journal of Proteome Research, 2023

Here, we introduce MSstats version 4.0 (v4.0), a statistical methodology and core package in the family of R/Bioconductor packages designed for statistical analysis of experiments with chromatography-based quantification.

Recommended citation: Kohler D, et al. MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale. J Proteome Res. 2023 May 5;22(5):1466-1482. https://pubs.acs.org/doi/10.1021/acs.jproteome.2c00834

MSstatsShiny: A GUI for Versatile, Scalable, and Reproducible Statistical Analyses of Quantitative Proteomic Experiments

Published in Journal of Proteome Research, 2023

This manuscript proposes a versatile statistical analysis framework that accurately detects relative changes in PTMs.

Recommended citation: Kohler D, et al. MSstatsShiny: A GUI for Versatile, Scalable, and Reproducible Statistical Analyses of Quantitative Proteomic Experiments. J Proteome Res. 2023 Feb 3;22(2):551-556. https://pubs.acs.org/doi/10.1021/acs.jproteome.2c00603

MSstatsPTM: Statistical Relative Quantification of Post-translational Modifications in Bottom-Up Mass Spectrometry-Based Proteomics

Published in Molecular & Cellular Proteomics, 2023

This manuscript proposes a versatile statistical analysis framework that accurately detects relative changes in PTMs.

Recommended citation: Kohler D, et al. MSstatsPTM: Statistical Relative Quantification of Posttranslational Modifications in Bottom-Up Mass Spectrometry-Based Proteomics. Mol Cell Proteomics. 2023 Jan;22(1):100477. https://www.mcponline.org/article/S1535-9476(22)00285-7/fulltext#secsectitle0020

Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications

Published in Nature Protocols, 2022

We introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins.

Recommended citation: Malinovska, L., Cappelletti, V., Kohler, D. et al. Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications. Nat Protoc 18, 659–682 (2023). https://www.nature.com/articles/s41596-022-00771-x

Recent Developments in MSstats Ecosystem: A collection of statistical methods for general scalable quantitative analysis of proteomic experiments.

Published in HUPO, 2022

The MSstats ecosystem is a family of open-source R/Bioconductor packages implementing statistical methods for quantitative mass spectrometry-based proteomic experiments. Here we review its recent developments, as well as advances in previously available methods and implementations.

Recommended citation: Kohler, D., Stankiak, M., & Vitek, O. (2022). Recent Developments in MSstats Ecosystem: A collection of statistical methods for general scalable quantitative analysis of proteomic experiments. HUPO News. https://hupo.org/News/12904194