{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T15:47:57Z","timestamp":1764604077335,"version":"3.41.2"},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"Supplement_1","license":[{"start":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T00:00:00Z","timestamp":1721692800000},"content-version":"vor","delay-in-days":22,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UAMS Winthrop P. Rockefeller Cancer Institute"},{"DOI":"10.13039\/100000001","name":"National Science Foundation Award","doi-asserted-by":"crossref","award":["OIA-1946391"],"award-info":[{"award-number":["OIA-1946391"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Institutes of Health National Institute of General Medical Sciences","award":["R24GM137786","P20GM121293"],"award-info":[{"award-number":["R24GM137786","P20GM121293"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This manuscript describes the development of a resource module that is part of a learning platform named \u2018NIGMS Sandbox for Cloud-based Learning\u2019 https:\/\/github.com\/NIGMS\/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on protein quantification in an interactive format that uses appropriate cloud resources for data access and analyses. Quantitative proteomics is a rapidly growing discipline due to the cutting-edge technologies of high resolution mass spectrometry. There are many data types to consider for proteome quantification including data dependent acquisition, data independent acquisition, multiplexing with Tandem Mass Tag reporter ions, spectral counts, and more. As part of the NIH NIGMS Sandbox effort, we developed a learning module to introduce students to mass spectrometry terminology, normalization methods, statistical designs, and basics of R programming. By utilizing the Google Cloud environment, the learning module is easily accessible without the need for complex installation procedures. The proteome quantification module demonstrates the analysis using a provided TMT10plex data set using MS3 reporter ion intensity quantitative values in a Jupyter notebook with an R kernel. The learning module begins with the raw intensities, performs normalization, and differential abundance analysis using limma models, and is designed for researchers with a basic understanding of mass spectrometry and R programming language. Learners walk away with a better understanding of how to navigate Google Cloud Platform for proteomic research, and with the basics of mass spectrometry data analysis at the command line.<\/jats:p>\n               <jats:p>This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https:\/\/github.com\/NIGMS\/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.<\/jats:p>","DOI":"10.1093\/bib\/bbae235","type":"journal-article","created":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T13:43:16Z","timestamp":1721742196000},"source":"Crossref","is-referenced-by-count":2,"title":["Understanding proteome quantification in an interactive learning module on Google Cloud Platform"],"prefix":"10.1093","volume":"25","author":[{"given":"Kyle A","family":"O\u2019Connell","sequence":"first","affiliation":[{"name":"National Institutes of Health Center for Information Technology, , 9000 Rockville Pike, Bethesda MD, 20892, United States"},{"name":"Deloitte Consulting LLP Health Data and AI, , 1919 N Lynn St, Arlington VA, 22209, United States"}]},{"given":"Benjamin","family":"Kopchick","sequence":"additional","affiliation":[{"name":"National Institutes of Health Center for Information Technology, , 9000 Rockville Pike, Bethesda MD, 20892, United States"},{"name":"Deloitte Consulting LLP Health Data and AI, , 1919 N Lynn St, Arlington VA, 22209, United States"}]},{"given":"Thad","family":"Carlson","sequence":"additional","affiliation":[{"name":"National Institutes of Health Center for Information Technology, , 9000 Rockville Pike, Bethesda MD, 20892, United States"},{"name":"Deloitte Consulting LLP Health Data and AI, , 1919 N Lynn St, Arlington VA, 22209, United States"}]},{"given":"David","family":"Belardo","sequence":"additional","affiliation":[{"name":"Google Cloud , 1900 Reston Metro Plz, Suite 1400, Reston VA, 20190, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1783-3610","authenticated-orcid":false,"given":"Stephanie D","family":"Byrum","sequence":"additional","affiliation":[{"name":"University of Arkansas for Medical Sciences Department of Biochemistry and Molecular Biology, , 4301 W. Markham St., Little Rock, AR, 72205, United States"},{"name":"Arkansas Children's Research Institute , 1 Children's Way, Little Rock, AR, 72202, United States"},{"name":"University of Arkansas for Medical Sciences Department of Biomedical Informatics, , 4301 W. Markham St, Little Rock, AR, 72205, United States"}]}],"member":"286","published-online":{"date-parts":[[2024,7,23]]},"reference":[{"journal-title":"Brief Bioinform","article-title":"NIGMS Sandbox: A Learning Platform toward Democratizing Cloud Computing for Biomedical Research","author":"Lei","key":"2024072312412316200_ref1"},{"key":"2024072312412316200_ref2","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"Limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2024072312412316200_ref3","doi-asserted-by":"crossref","DOI":"10.21105\/joss.05184","article-title":"proteoDA: a package for quantitative proteomics","volume":"8","author":"Thurman","year":"2023","journal-title":"J Open Source Softw"},{"key":"2024072312412316200_ref4","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1039\/D1MO00117E","article-title":"Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer","volume":"17","author":"Chappell","year":"2021","journal-title":"Mol Omics"},{"key":"2024072312412316200_ref5","doi-asserted-by":"crossref","first-page":"25625","DOI":"10.1021\/acsomega.0c02564","article-title":"proteiNorm \u2013 a user-friendly tool for normalization and analysis of TMT and label-free protein quantification","volume":"5","author":"Graw","year":"2020","journal-title":"ACS Omega"},{"key":"2024072312412316200_ref6","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.12688\/f1000research.27893.1","article-title":"A guide to creating design matrices for gene expression experiments","volume":"9","author":"Law","year":"2020","journal-title":"F1000Res"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/Supplement_1\/bbae235\/58618821\/bbae235.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/Supplement_1\/bbae235\/58618821\/bbae235.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T13:43:27Z","timestamp":1721742207000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbae235\/7718481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7]]},"references-count":6,"journal-issue":{"issue":"Supplement_1","published-print":{"date-parts":[[2024,7,23]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbae235","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"type":"print","value":"1467-5463"},{"type":"electronic","value":"1477-4054"}],"subject":[],"published-other":{"date-parts":[[2024,7]]},"published":{"date-parts":[[2024,7]]},"article-number":"bbae235"}}