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Cited by 288

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

The statistical properties of gene-set analysis

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de Leeuw, Christiaan A., Neale, Benjamin M., Heskes, Tom, Posthuma, Danielle·2016·Nature Reviews Genetics

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Show all 16 references

Research works printed but not linked: 26

  1. Wang, K., Li, M. & Hakonarson, H. Analysing biological pathways in genome-wide association studies. Nat. Rev. Genet. 11, 843–854 (2010). This review provides a comprehensive overview of the basic concepts and issues relevant to gene-set analysis. · DOI · Paper page
  2. Sullivan, P. F. & Posthuma, D. Biological pathways and networks implicated in psychiatric disorders. Curr. Opin. Behav. Sci. 2, 58–68 (2015). · DOI
  3. Nurnberger, J. I. et al. Identification of pathways for bipolar disorder: a meta-analysis. JAMA Psychiatry 71, 657–664 (2014). · DOI · Paper page
  4. Askland, K., Read, C. & Moore, J. Pathway-based analyses of whole-genome association study data in bipolar disorder reveal genes mediating ion channel activity and synaptic neurotransmission. Hum. Genet. 125, 63–79 (2009). · DOI
  5. Eleftherohorinou, H., Hoggart, C. J., Wright, V. J., Levin, M. & Coin, L. J. Pathway-driven gene stability selection of two rheumatoid arthritis GWAS identifies and validates new susceptibility genes in receptor mediated signalling pathways. Hum. Mol. Genet. 20, 3494–3506 (2011). · DOI
  6. Menashe, I. et al. Pathway analysis of breast cancer genome-wide association study highlights three pathways and one canonical signaling cascade. Cancer Res. 70, 4453–4459 (2010). · DOI
  7. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Genome-wide association study identifies five new schizophrenia loci. Nat. Genet. 43, 969–976 (2011). · DOI · Paper page
  8. Manolio, T. A. Genomewide association studies and assessment of the risk of disease. N. Engl. J. Med. 363, 166–176 (2010). · DOI · Paper page
  9. Manolio, T. A. Bringing genome-wide association findings into clinical use. Nat. Rev. Genet. 14, 549–558 (2013). · DOI · Paper page
  10. Qian, D. C. et al. Identification of shared and unique susceptibility pathways among cancers of the lung, breast, and prostate from genome-wide association studies and tissue-specific protein interactions. Hum. Mol. Genet. 24, 7406–7420 (2015). · DOI
  11. Croft, D., Mundo, A. F., Haw, R., Milacic, M. & Weiser, J. The Reactome pathway knowledgebase. Nucleic Acids Res. 42, D472–D477 (2014). This is a clear practical guide to carrying out a gene-set analysis. · DOI · Paper page
  12. Mooney, M. A., Nigg, J. T., McWeeney, S. K. & Wilmot, B. Functional and genomic context in pathway analysis of GWAS data. Trends Genet. 30, 390–400 (2014). · DOI
  13. Holmans, P. Statistical methods for pathway analysis of genome-wide data for association with complex genetic traits. Adv. Genet. 72, 141–179 (2010). This paper provides an extensive theoretical overview of different types of methods and sources of gene sets. · DOI
  14. Evangelou, M., Rendon, A., Ouwehand, W. H., Wernisch, L. & Dudbridge, F. Comparison of methods for competitive tests of pathway analysis. PLoS ONE 7, e41018 (2012). · DOI
  15. Gui, H., Li, M., Sham, P. C. & Cherny, S. S. Comparison of seven algorithms for pathway analysis using the WTCCC Crohn's Disease dataset. BMC Res. Notes 4, 386 (2011). · DOI
  16. Elbers, C. C. et al. Using genome-wide pathway analysis to unravel the etiology of complex diseases. Genet. Epidemiol. 33, 419–431 (2009). · DOI · Paper page
  17. Tintle, N. L., Borchers, B., Brown, M. & Bekmetjev, A. Comparing gene set analysis methods on single-nucleotide polymorphism data from Genetic Analysis Workshop 16. BMC Proc. 3, S96 (2009). · DOI
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  19. Moskvina, V. et al. Evaluation of an approximation method for assessment of overall significance of multiple-dependent tests in a genome-wide association study. Genet. Epidemiol. 35, 861–866 (2011). · DOI · Paper page
  20. O'Dushlaine, C. et al. The SNP ratio test: pathway analysis of genome-wide association datasets. Bioinformatics 25, 2762–2763 (2009). · DOI
  21. Li, M., Kwan, J. S. H. & Sham, P. C. HYST: a hybrid set-based test for genome-wide association studies, with application to protein-protein interaction-based association analysis. Am. J. Hum. Genet. 91, 478–488 (2012). · DOI
  22. Pedroso, I. et al. Common genetic variants and gene-expression changes associated with bipolar disorder are over-represented in brain signaling pathway genes. Biol. Psychiatry 72, 311–317 (2012). · DOI · Paper page
  23. Wang, K., Li, M. & Bucan, M. Pathway-based approaches for analysis of genome-wide association studies. Am. J. Hum. Genet. 81, 1278–1283 (2007). · DOI · Paper page
  24. Lee, P. H., O'Dushlaine, C., Thomas, B. & Purcell, S. M. INRICH: Interval-based enrichment analysis for genome-wide association studies. Bioinformatics 28, 1797–1799 (2012). · DOI · Paper page
  25. Jia, P. & Zhao, Z. Network-assisted analysis to prioritize GWAS results: princples, methods and perspectives. Hum. Genet. 133, 125–138 (2014). · DOI
  26. Mitrea, C. et al. Methods and approaches in the topology-based analysis of biological pathways. Front. Physiol. 4, 278 (2013). · DOI · Paper page

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Metadata

Authors
de Leeuw, C. A., Neale, B. M., Heskes, T., & Posthuma, D.
Venue
Nature Reviews Genetics
Published
2016-04-12
Volume
17
Issue
6
Pages
353-364
ISSN
  • 1471-0056 (ISSN-L)
  • 1471-0064
OpenAlex
W2341504574
Cited by
288
References
16
FWCI
2.48
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

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de Leeuw, C. A., Neale, B. M., Heskes, T., & Posthuma, D. (2016). The statistical properties of gene-set analysis. Nature Reviews Genetics. https://doi.org/10.1038/nrg.2016.29

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