The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Statistical Design of Quantitative Mass Spectrometry-Based Proteomic Experiments
Abstract
We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.
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Cites
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Protein biomarker discovery and validation: the long and uncertain path to clinical utility
Rifai, N., Gillette, M. A., & Carr, S. A. (2006) · Nature Biotechnology · doi:10.1038/nbt1235 · Cited by 1,867
Mann, C. J. (2003) · Emergency Medicine Journal · doi:10.1136/emj.20.1.54 · Cited by 1,558
Cited by
Bruderer, R., Bernhardt, O. M., Gandhi, T., Miladinović, S. M., Cheng, L.-Y., Messner, S., Ehrenberger, T., Zanotelli, V., Butscheid, Y., Escher, C., et al. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.044305 · Cited by 1,238
Self-citationCarr, S. A., Abbatiello, S. E., Ackermann, B. L., Borchers, C., Domon, B., Deutsch, E. W., Grant, R. P., Hoofnagle, A. N., Hüttenhain, R., Koomen, J. M., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.036095 · Cited by 561
Self-citationmProphet: automated data processing and statistical validation for large-scale SRM experiments
Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Brusniak, M.-Y., Hengartner, M. O., & Aebersold, R. (2011) · Nature Methods · doi:10.1038/nmeth.1584 · Cited by 532
High‐Throughput Metabolomics by 1D NMR
Vignoli, A., Ghini, V., Meoni, G., Licari, C., Takis, P. G., Tenori, L., Turano, P., & Luchinat, C. (2019) · Angewandte Chemie International Edition · doi:10.1002/anie.201804736 · Cited by 365
Gillet, L. C., Leitner, A., & Aebersold, R. (2016) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-071015-041535 · Cited by 323
Metadata
- Authors
- Oberg, A. L., & Vitek, O.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-03-27
- Volume
- 8
- Issue
- 5
- Pages
- 2144-2156
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W1984971566
- Cited by
- 256
- References
- 5
- FWCI
- 7.84
- Type
- journal article
- Language
- en
- Open access
- closed
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