MaxQuant and MSstats in Galaxy enable reproducible cloud-based analysis of quantitative proteomics experiments for everyone
MaxQuant and MSstats in Galaxy enable reproducible cloud-based analysis of quantitative proteomics experiments for everyone
ABSTRACT Quantitative mass spectrometry-based proteomics has become a high-throughput technology for the identification and quantification of thousands of proteins in complex biological samples. Two de facto standard tools, MaxQuant and MSstats, allow for the analysis of raw data and finding proteins with differential abundance between conditions of interest. To enable accessible and reproducible quantitative proteomics analyses in a cloud environment, we have integrated MaxQuant (including TMTpro 16/18plex), Proteomics Quality Control (PTXQC), MSstats and MSstatsTMT into the open-source Galaxy framework. This enables the web-based analysis of label-free and isobaric labeling proteomics experiments via Galaxy’s graphical user interface on public clouds. MaxQuant and MSstats in Galaxy can be applied in conjunction with thousands of existing Galaxy tools and integrated into standardized, sharable workflows. Galaxy tracks all metadata and intermediate results in analysis histories, which can be shared privately for collaborations or publicly, allowing full reproducibility and transparency of published analysis. To further increase accessibility, we provide detailed hands-on training materials. The integration of MaxQuant and MSstats into the Galaxy framework enables their usage in a reproducible way on accessible large computational infrastructures, hence realizing the foundation for high throughput proteomics data science for everyone.
Johnson James、Gr¨1ning Bj?rn Andreas、Drepper Friedel、F?ll Melanie Christine、Schilling Oliver、Fahrner Matthias、Fr?hlich Klemens、Pinter Niko、Gl?tzer Damian、Warscheid Bettina
Minnesota Supercomputing Institute, University of MinnesotaDepartment of Computer Science, University of FreiburgBiochemistry and Functional Proteomics, Institute of Biology II, Faculty of Biology, University of FreiburgInstitute for Surgical Pathology, Medical Center ¨C University of Freiburg||Faculty of Medicine - University of Freiburg||Khoury College of Computer Sciences, Northeastern UniversityInstitute for Surgical Pathology, Medical Center ¨C University of Freiburg||Faculty of Medicine - University of Freiburg||German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ)Institute for Surgical Pathology, Medical Center ¨C University of Freiburg||Faculty of Medicine - University of Freiburg||Faculty of Biology, University of FreiburgInstitute for Surgical Pathology, Medical Center ¨C University of Freiburg||Faculty of Medicine - University of Freiburg||Faculty of Biology, University of Freiburg||Spemann Graduate School of Biology and Medicine (SGBM), Albert-Ludwigs-University FreiburgInstitute for Surgical Pathology, Medical Center ¨C University of Freiburg||Faculty of Medicine - University of FreiburgBiochemistry and Functional Proteomics, Institute of Biology II, Faculty of Biology, University of FreiburgBiochemistry and Functional Proteomics, Institute of Biology II, Faculty of Biology, University of Freiburg||Faculty of Chemistry and Pharmacy, Department of Biochemistry
生物科学研究方法、生物科学研究技术计算技术、计算机技术
LC-MS/MStandem mass spectrometryproteomicsbioinformaticsstatistical modelingcloud computingreproducibility
Johnson James,Gr¨1ning Bj?rn Andreas,Drepper Friedel,F?ll Melanie Christine,Schilling Oliver,Fahrner Matthias,Fr?hlich Klemens,Pinter Niko,Gl?tzer Damian,Warscheid Bettina.MaxQuant and MSstats in Galaxy enable reproducible cloud-based analysis of quantitative proteomics experiments for everyone[EB/OL].(2025-03-28)[2025-06-19].https://www.biorxiv.org/content/10.1101/2022.01.20.477129.点此复制
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