Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam Principles)
- PMID: 22053864
- PMCID: PMC3272102
- DOI: 10.1021/pr201071t
Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam Principles)
Abstract
Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: (1) an evolving list of comprehensive quality metrics and (2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.
References
-
- [accessed May 11, 2011];Policies on Release of Human Genomic Sequence Data. http://www.ornl.gov/sci/techresources/Human_Genome/research/bermuda.shtml.
- [accessed May 11, 2011];Sharing Data from Large-sclae Biological Research Projects: A System of Tripartite Responsibility. http://www.wellcome.ac.uk/stellent/groups/corporatesite/@policy_communic....
-
- Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, Aach J, Ansorge W, Ball CA, Causton HC, Gaasterland T, Glenisson P, Holstege FC, Kim IF, Markowitz V, Matese JC, Parkinson H, Robinson A, Sarkans U, Schulze-Kremer S, Stewart J, Taylor R, Vilo J, Vingron M. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet. 2001;29(4):365–71. - PubMed
-
- Carr S, Aebersold R, Baldwin M, Burlingame A, Clauser K, Nesvizhskii A. The Need for Guidelines in Publication of Peptide and Protein Identification Data: Working Group On Publication Guidelines For Peptide And Protein Identification Data. Mol Cell Proteomics. 2004;3(6):531–533. - PubMed
-
- Wilkins MR, Appel RD, Van Eyk JE, Chung MCM, Görg A, Hecker M, Huber LA, Langen H, Link AJ, Paik YK, Patterson SD, Pennington SR, Rabilloud T, Simpson RJ, Weiss W, Dunn MJ. Guidelines for the next 10 years of proteomics. Proteomics. 2006;6(1):4–8. - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
