The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets
Open accessAbstract
Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average, 75% of spectra analyzed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large scale to shed light on these unidentified spectra. The Proteomics Identifications (PRIDE) Database Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in the PRIDE Archive, coming from hundreds of data sets, we were able to consistently characterize spectra into three distinct groups: (1) incorrectly identified, (2) correctly identified but below the set scoring threshold, and (3) truly unidentified. Using multiple complementary analysis approaches, we were able to identify ∼20% of the consistently unidentified spectra. The complete spectrum-clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.
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Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
Desiere, F. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj040 · Cited by 910
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Metadata
- Authors
- Griss, J., Perez-Riverol, Y., Lewis, S., Tabb, D. L., Dianes, J. A., del-Toro, N., Rurik, M., Walzer, M., Kohlbacher, O., Hermjakob, H., Wang, R., & Vizcaíno, J. A.
- Venue
- Nature Methods
- Published
- 2016-06-27
- Volume
- 13
- Issue
- 8
- Pages
- 651-656
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2465480251
- Cited by
- 179
- References
- 2
- FWCI
- 10.27
- Type
- journal article
- Language
- en
- Open access
- green
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- Griss, J., Perez-Riverol, Y., Lewis, S., Tabb, D. L., Dianes, J. A., del-Toro, N., Rurik, M., Walzer, M., Kohlbacher, O., Hermjakob, H., Wang, R., & Vizcaíno, J. A. (2016). Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets. Nature Methods. https://doi.org/10.1038/nmeth.3902
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