The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
DAnTE: a statistical tool for quantitative analysis of -omics data
Open accessAbstract
Summary: Data Analysis Tool Extension (DAnTE) is a statistical tool designed to address challenges associated with quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected normalization methods, missing value imputation algorithms, peptide-to-protein rollup methods, an extensive array of plotting functions and a comprehensive hypothesis-testing scheme that can handle unbalanced data and random effects. The graphical user interface (GUI) is designed to be very intuitive and user friendly. Availability: DAnTE may be downloaded free of charge at http://omics.pnl.gov/software/ Contact: rds@pnl.gov or proteomics@pnl.gov Supplementary information: An example dataset with instructions on how to perform a series of analysis steps is available at http://omics.pnl.gov/software/
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Cited by
Cox, J., Hein, M. Y., Luber, C. A., Paron, I., Nagaraj, N., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.031591 · Cited by 5,180
Proteogenomic and metabolomic characterization of human glioblastoma
Wang, L.-B., Karpova, A., Gritsenko, M. A., Kyle, J. E., Cao, S., Li, Y., Rykunov, D., Colaprico, A., Rothstein, J. H., Hong, R., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.01.006 · Cited by 661
Self-citationNormalization and missing value imputation for label-free LC-MS analysis
Karpievitch, Y. V., Dabney, A. R., & Smith, R. D. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-s16-s5 · Cited by 345
Self-citationWebb-Robertson, B.-J. M., Wiberg, H. K., Matzke, M. M., Brown, J. N., Wang, J., McDermott, J. E., Smith, R. D., Rodland, K. D., Metz, T. O., Pounds, J. G., et al. (2015) · Journal of Proteome Research · doi:10.1021/pr501138h · Cited by 294
Self-citationA statistical framework for protein quantitation in bottom-up MS-based proteomics
Karpievitch, Y., Stanley, J., Taverner, T., Huang, J., Adkins, J. N., Ansong, C., Heffron, F., Metz, T. O., Qian, W.-J., Yoon, H., et al. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp362 · Cited by 176
Metadata
- Authors
- Polpitiya, A. D., Qian, W.-J., Jaitly, N., Petyuk, V. A., Adkins, J. N., Camp, D. G., Anderson, G. A., & Smith, R. D.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-05-03
- Volume
- 24
- Issue
- 13
- Pages
- 1556-1558
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2147830145
- Cited by
- 435
- References
- 18
- FWCI
- 8.56
- Type
- journal article
- Language
- en
- Open access
- green
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- Polpitiya, A. D., Qian, W.-J., Jaitly, N., Petyuk, V. A., Adkins, J. N., Camp, D. G., Anderson, G. A., & Smith, R. D. (2008). DAnTE: a statistical tool for quantitative analysis of -omics data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btn217
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