P. McGarvey, Ratna R. Thangudu, Junfeng Ma, Ci Wu, Shabeeb Kannattikuni, Krysta Chaldekas, D. Berry, Alicia Francis, D. Singhal, P. Rudnick, An, Basu, Subha Madhavan
{"title":"Sharing Data from an Academic Cancer Center Biospecimen and Proteomic Core Facilities through the Proteomics Data Commons","authors":"P. McGarvey, Ratna R. Thangudu, Junfeng Ma, Ci Wu, Shabeeb Kannattikuni, Krysta Chaldekas, D. Berry, Alicia Francis, D. Singhal, P. Rudnick, An, Basu, Subha Madhavan","doi":"10.35248/0974-276X.21.14.529","DOIUrl":null,"url":null,"abstract":"Data sharing is critical for open science and often required by funding organizations and journals. NCI has developed the Proteomics Data Commons (PDC) as part of the Cancer Research Data Commons, an infrastructure that allows users to share, analyze, and store results, utilizing the storage and compute resources of the cloud. To date most of the data available in the various Data Commons are submitted from large multi-institution research programs funded by NCI with teams of specialists from multiple scientific disciplines. Here we describe our experiences and summarize the recommended best practices for sharing a set of proteomics and related biospecimen data and analyses results from smaller scale proteomics studies conducted in an academic medical center core facility using patient samples of lung adenocarcinoma. Mapping and depositing data in the manner described here harmonizes user’s data to a common data model and community standards, making it possible to view the data alongside other high value cancer studies available in the PDC. Availability: Data, metadata, protocols with peptide and protein identifications are available at the PDC. (https:// pdc.cancer.gov/pdc/study/PDC000231).","PeriodicalId":73911,"journal":{"name":"Journal of proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35248/0974-276X.21.14.529","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
Data sharing is critical for open science and often required by funding organizations and journals. NCI has developed the Proteomics Data Commons (PDC) as part of the Cancer Research Data Commons, an infrastructure that allows users to share, analyze, and store results, utilizing the storage and compute resources of the cloud. To date most of the data available in the various Data Commons are submitted from large multi-institution research programs funded by NCI with teams of specialists from multiple scientific disciplines. Here we describe our experiences and summarize the recommended best practices for sharing a set of proteomics and related biospecimen data and analyses results from smaller scale proteomics studies conducted in an academic medical center core facility using patient samples of lung adenocarcinoma. Mapping and depositing data in the manner described here harmonizes user’s data to a common data model and community standards, making it possible to view the data alongside other high value cancer studies available in the PDC. Availability: Data, metadata, protocols with peptide and protein identifications are available at the PDC. (https:// pdc.cancer.gov/pdc/study/PDC000231).