Produção Nacional
Revisado por pares
Toward More Transparent and Reproducible Omics Studies Through a Common Metadata Checklist and Data Publications
2013; Mary Ann Liebert, Inc.; Volume: 1; Issue: 4 Linguagem: Inglês
10.1089/big.2013.0039
ISSN2167-647X
AutoresEugene Kolker, Vural Özdemir, Lennart Martens, William S. Hancock, Gordon Anderson, Nathaniel Anderson, Şükrü Aynacıoğlu, Ancha Baranova, Shawn R. Campagna, Rui Chen, John Choiniere, Stephen P. Dearth, Wu-chun Feng, Lynnette R. Ferguson, Geoffrey Fox, Dmitrij Frishman, Robert L. Grossman, Allison P. Heath, Roger Higdon, Mara Helena Hutz, Imre Janko, Lihua Jiang, Sanjay Joshi, Alexander Kel, Joseph W. Kemnitz, Isaac S. Kohane, Natali Kolker, Doron Lancet, Elaine Lee, Weizhong Li, Andrey Lisitsa, Adrián LLerena, Courtney MacNealy-Koch, Jean-Claude Marshall, Paola Masuzzo, Amanda L. May, George I. Mias, Matthew Monroe, Elizabeth Montague, Sean D. Mooney, Alexey I. Nesvizhskii, Santosh Noronha, Gilbert S. Omenn, Harsha Rajasimha, Preveen Ramamoorthy, Jerry Sheehan, Larry Smarr, Charles V. Smith, Todd Smith, M Snyder, Srikanth Rapole, Sanjeeva Srivastava, Larissa Stanberry, Elizabeth Stewart, Stefano Toppo, Peter Uetz, Kenneth Verheggen, Brynn H. Voy, Louise Warnich, Steven W. Wilhelm, Gregory Yandl,
Tópico(s)Bioinformatics and Genomic Networks
ResumoBiological processes are fundamentally driven by complex interactions between biomolecules. Integrated high-throughput omics studies enable multifaceted views of cells, organisms, or their communities. With the advent of new post-genomics technologies, omics studies are becoming increasingly prevalent; yet the full impact of these studies can only be realized through data harmonization, sharing, meta-analysis, and integrated research. These essential steps require consistent generation, capture, and distribution of metadata. To ensure transparency, facilitate data harmonization, and maximize reproducibility and usability of life sciences studies, we propose a simple common omics metadata checklist. The proposed checklist is built on the rich ontologies and standards already in use by the life sciences community. The checklist will serve as a common denominator to guide experimental design, capture important parameters, and be used as a standard format for stand-alone data publications. The omics metadata checklist and data publications will create efficient linkages between omics data and knowledge-based life sciences innovation and, importantly, allow for appropriate attribution to data generators and infrastructure science builders in the post-genomics era. We ask that the life sciences community test the proposed omics metadata checklist and data publications and provide feedback for their use and improvement.
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