Ziyi Li, Cory A Weller, Syed Shah, Nicholas L Johnson, Ying Hao, Paige B Jarreau, Jessica Roberts, Deyaan Guha, Colleen Bereda, Sydney Klaisner, Pedro Machado, Matteo Zanovello, Mercedes Prudencio, Björn Oskarsson, Nathan P Staff, Dennis W Dickson, Pietro Fratta, Leonard Petrucelli, Priyanka Narayan, Mark R Cookson, Michael E Ward, Andrew B Singleton, Mike A Nalls, Yue A Qi
{"title":"ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics.","authors":"Ziyi Li, Cory A Weller, Syed Shah, Nicholas L Johnson, Ying Hao, Paige B Jarreau, Jessica Roberts, Deyaan Guha, Colleen Bereda, Sydney Klaisner, Pedro Machado, Matteo Zanovello, Mercedes Prudencio, Björn Oskarsson, Nathan P Staff, Dennis W Dickson, Pietro Fratta, Leonard Petrucelli, Priyanka Narayan, Mark R Cookson, Michael E Ward, Andrew B Singleton, Mike A Nalls, Yue A Qi","doi":"10.1093/gpbjnl/qzae083","DOIUrl":null,"url":null,"abstract":"<p><p>Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, with personalized medicine, systems biology, and biomedical applications. The application of MS-based proteomics advances our understanding of protein function, cellular signaling, and complex biological systems. MS data analysis is a critical process that includes identifying and quantifying proteins and peptides and then exploring their biological functions in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets with DIA-NN preinstalled. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analyses. ProtPipe provides downstream analyses, including protein and peptide differential abundance identification, pathway enrichment analysis, protein-protein interaction analysis, and Major histocompatibility complex (MHC) -peptide binding affinity analysis. ProtPipe generates annotated tables and visualizations by performing statistical postprocessing and calculating fold changes between predefined pairwise conditions in an experimental design. It is an open-source, well-documented tool available online at https://github.com/NIH-CARD/ProtPipe, with a user-friendly web interface.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics, proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/gpbjnl/qzae083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, with personalized medicine, systems biology, and biomedical applications. The application of MS-based proteomics advances our understanding of protein function, cellular signaling, and complex biological systems. MS data analysis is a critical process that includes identifying and quantifying proteins and peptides and then exploring their biological functions in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets with DIA-NN preinstalled. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analyses. ProtPipe provides downstream analyses, including protein and peptide differential abundance identification, pathway enrichment analysis, protein-protein interaction analysis, and Major histocompatibility complex (MHC) -peptide binding affinity analysis. ProtPipe generates annotated tables and visualizations by performing statistical postprocessing and calculating fold changes between predefined pairwise conditions in an experimental design. It is an open-source, well-documented tool available online at https://github.com/NIH-CARD/ProtPipe, with a user-friendly web interface.