@article{hinzke_kunath_blakeley-ruiz_korenek_vintila_wilmes_kleiner_2025, title={Comprehensive evaluation of statistical approaches for differential metaproteomics}, volume={12}, url={https://doi.org/10.64898/2025.12.10.693402}, DOI={10.64898/2025.12.10.693402}, abstractNote={We highlight key recommendations for differential expression analysis in metaproteomics. Our work enables improved assessment of statistical methods for metaproteomics by establishing a framework for testing statistical approaches, including comprehensive raw mass spectrometry data and reproducible benchmarking code.}, author={Hinzke, Tjorven and Kunath, Benoit J. and Blakeley-Ruiz, J. Alfredo and Korenek, Abigail and Vintila, Simina and Wilmes, Paul and Kleiner, Manuel}, year={2025}, month={Dec} }
 @article{hinzke_kunath_blakeley-ruiz_korenek_vintila_wilmes_kleiner_2025, title={Evaluation of statistical approaches for differential metaproteomics: Reproducible code}, DOI={10.5281/zenodo.17880378}, abstractNote={Reproducible code for recommended tests for statistical analysis of metaproteomics datasets, including the protein group quantification files needed, and an explanation of how to use the code (README). Acknowledgements This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Transregio Collaborative Research Centre 410 "WETSCAPES2.0", the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R35GM138362, the US National Science Foundation (NSF, IOS #2421771), the Novo Nordisk Foundation (INTERACT, Grant number: NNF19SA0059360), the U.S. Department of Agriculture National Institute of Food and Agriculture under award No. 2022-67013-36672, the US Department of Energy (DE-SC0022996), and a National Research Fund Luxembourg (FNR) grant (number INTER/Mobility/2022/BM/16965254). We thank Michael Greenacre for help with the chiPower transformation, and Philipp Adämmer for input on XGBoost. Elisa Kasbohm and Volkmar Liebscher provided valuable discussions on statistics. We thank Heather Maughan for valuable comments on the manuscript. The Gnotobiotic Core at the College of Veterinary Medicine, North Carolina State University is supported by the National Institutes of Health funded Center for Gastrointestinal Biology and Disease, NIH-NIDDK P30 DK034987. All LC-MS/MS measurements were made in the Molecular Education, Technology, and Research Innovation Center (METRIC) at North Carolina State University.}, journal={Zenodo (CERN European Organization for Nuclear Research)}, author={Hinzke, Tjorven and Kunath, Benoit J. and Blakeley-Ruiz, Jose Alfredo and Korenek, Abigail and Vintila, Simina and Wilmes, Paul and Kleiner, Manuel}, year={2025}, month={Dec} }
 @article{hinzke_kunath_blakeley-ruiz_korenek_vintila_wilmes_kleiner_2025, title={Evaluation of statistical approaches for differential metaproteomics: Reproducible code}, DOI={10.5281/zenodo.17880379}, abstractNote={Reproducible code for recommended tests for statistical analysis of metaproteomics datasets, including the protein group quantification files needed, and an explanation of how to use the code (README). Acknowledgements This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Transregio Collaborative Research Centre 410 "WETSCAPES2.0", the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R35GM138362, the US National Science Foundation (NSF, IOS #2421771), the Novo Nordisk Foundation (INTERACT, Grant number: NNF19SA0059360), the U.S. Department of Agriculture National Institute of Food and Agriculture under award No. 2022-67013-36672, the US Department of Energy (DE-SC0022996), and a National Research Fund Luxembourg (FNR) grant (number INTER/Mobility/2022/BM/16965254). We thank Michael Greenacre for help with the chiPower transformation, and Philipp Adämmer for input on XGBoost. Elisa Kasbohm and Volkmar Liebscher provided valuable discussions on statistics. We thank Heather Maughan for valuable comments on the manuscript. The Gnotobiotic Core at the College of Veterinary Medicine, North Carolina State University is supported by the National Institutes of Health funded Center for Gastrointestinal Biology and Disease, NIH-NIDDK P30 DK034987. All LC-MS/MS measurements were made in the Molecular Education, Technology, and Research Innovation Center (METRIC) at North Carolina State University.}, journal={Zenodo (CERN European Organization for Nuclear Research)}, author={Hinzke, Tjorven and Kunath, Benoit J. and Blakeley-Ruiz, Jose Alfredo and Korenek, Abigail and Vintila, Simina and Wilmes, Paul and Kleiner, Manuel}, year={2025}, month={Dec} }
 @article{bossche_armengaud_benndorf_blakeley‐ruiz_brauer_cheng_creskey_figeys_grenga_griffin_et al._2025, title={The microbiologist's guide to metaproteomics}, volume={5}, url={http://dx.doi.org/10.1002/imt2.70031}, DOI={10.1002/imt2.70031}, abstractNote={Metaproteomics is an emerging approach for studying microbiomes, offering the ability to characterize proteins that underpin microbial functionality within diverse ecosystems. As the primary catalytic and structural components of microbiomes, proteins provide unique insights into the active processes and ecological roles of microbial communities. By integrating metaproteomics with other omics disciplines, researchers can gain a comprehensive understanding of microbial ecology, interactions, and functional dynamics. This review, developed by the Metaproteomics Initiative (www.metaproteomics.org), serves as a practical guide for both microbiome and proteomics researchers, presenting key principles, state-of-the-art methodologies, and analytical workflows essential to metaproteomics. Topics covered include experimental design, sample preparation, mass spectrometry techniques, data analysis strategies, and statistical approaches.}, journal={iMeta}, author={Bossche, Tim Van Den and Armengaud, Jean and Benndorf, Dirk and Blakeley‐Ruiz, Jose Alfredo and Brauer, Madita and Cheng, Kai and Creskey, Marybeth and Figeys, Daniel and Grenga, Lucia and Griffin, Timothy J. and et al.}, year={2025}, month={May} }