The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
On testing the significance of sets of genes
Open accessAbstract
This paper discusses the problem of identifying differentially expressed groups of genes from a microarray experiment. The groups of genes are externally defined, for example, sets of gene pathways derived from biological databases. Our starting point is the interesting Gene Set Enrichment Analysis (GSEA) procedure of Subramanian et al. [Proc. Natl. Acad. Sci. USA 102 (2005) 15545–15550]. We study the problem in some generality and propose two potential improvements to GSEA: the maxmean statistic for summarizing gene-sets, and restandardization for more accurate inferences. We discuss a variety of examples and extensions, including the use of gene-set scores for class predictions. We also describe a new R language package GSA that implements our ideas.
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Transcriptional profiling of aging in human muscle reveals a common aging signature
Zahn, J. M., Sonu, R., Vogel, H., Crane, E., Mazan-Mamczarz, K., Rabkin, R., Davis, R. W., Becker, K. G., Owen, A. B., & Kim, S. K. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020115 · Cited by 351
Cited by
GSVA: gene set variation analysis for microarray and RNA-Seq data
Hänzelmann, S., Castelo, R., & Guinney, J. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-7 · Cited by 15,440
The consensus molecular subtypes of colorectal cancer
Guinney, J., Dienstmann, R., Wang, X., de Reyniès, A., Schlicker, A., Soneson, C., Marisa, L., Roepman, P., Nyamundanda, G., Angelino, P., et al. (2015) · Nature Medicine · doi:10.1038/nm.3967 · Cited by 5,170
Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer
Twyman-Saint Victor, C., Rech, A. J., Maity, A., Rengan, R., Pauken, K. E., Stelekati, E., Benci, J. L., Xu, B., Dada, H., Odorizzi, P. M., et al. (2015) · Nature · doi:10.1038/nature14292 · Cited by 2,434
Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis
Xia, J., & Wishart, D. S. (2016) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.11 · Cited by 1,544
Deletion of IKZF1 and Prognosis in Acute Lymphoblastic Leukemia
Mullighan, C. G., Su, X., Zhang, J., Radtke, I., Phillips, L. A. A., Miller, C. B., Ma, J., Liu, W., Cheng, C., Schulman, B. A., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0808253 · Cited by 1,422
Metadata
- Authors
- Efron, B., & Tibshirani, R.
- Venue
- The Annals of Applied Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 2007-06-01
- Volume
- 1
- Issue
- 1
- Pages
- 107-129
- ISSN
- 1932-6157 (ISSN-L)
- OpenAlex
- W2020859582
- Cited by
- 798
- References
- 4
- FWCI
- 20.11
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
