Weighted gene coexpression network analysis: State of the art

Journal of Biopharmaceutical Statistics

Volumn 20, Issue 2, 2010, Pages 281-300

  Zhao, Wei ^a   Langfelder, Peter ^b   Fuller, Tova ^b   Dong, Jun ^d   Li, Ai ^e   Hovarth, Steve ^b,c  

^a ST JUDE CHILDREN S RESEARCH HOSPITAL   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d AMGEN INC   (United States)

^e NOVARTIS PHARMA AG   (Switzerland)

Author keywords

Cancer; Gene expression; Network; WGCNA

Indexed keywords

BAYES THEOREM; BRAIN FUNCTION; CHIMPANZEE; CLUSTER ANALYSIS; EXPLORATORY RESEARCH; GENE EXPRESSION; GLIOBLASTOMA; HUMAN; HYPOTHESIS; INDEPENDENT VARIABLE; METHODOLOGY; NONHUMAN; ONCOGENE; ONCOLOGY; PRIORITY JOURNAL; PROTEIN INTERACTION; REVIEW; SCREENING; SOCIAL NETWORK; STATISTICAL ANALYSIS; VALIDATION STUDY; WEIGHTED GENE COEXPRESSION NETWORK ANALYSIS;

ANIMALS; BAYES THEOREM; BRAIN; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; GENE REGULATORY NETWORKS; HUMANS; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PAN TROGLODYTES; PROTEIN INTERACTION MAPPING; RNA, MESSENGER; SPECIES SPECIFICITY;

EID: 77951274224     PISSN: 10543406     EISSN: 15205711     Source Type: Journal    
DOI: 10.1080/10543400903572753     Document Type: Review

References (29)

1. Albert, R., Jeong, H., Barabasi, A. L. (2000). Error and attack tolerance of complex networks. Nature 406:378-381.
2. Arnone, M. I., Davidson, E. H. (1997). The hardwiring of development: organization and function of genomic regulatory systems. Development 124(10):1851-1864.
3. Aten, J. E., Fuller, T. F., Lusis, A. J., Horvath, S. (2008). Using genetic markers to orient the edges in quantitative traite networks: the NEO software. BMC Syst. Biol. 2:34.
4. Barabasi, A. L., Albert, R. (1999). Emergence of scaling in random networks. Science 286:509-512.
5. Barabasi, A. L., Bonabeau, C. (2003). Scale-free networks. Sci. Am. May:60-69.
6. Benjamini, Y., Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57:289-300.
7. Benjamini, Y., Hochberg, Y. (2000). On the adaptive control of the false discovery rate in multiple testing with independent statistics. J. Edu. Behav. Stat. 25:60-83.
8. Carlson, M. R. J., Zhang, B., Fang, Z., Mischel, P. S., Horvath, S., Nelson, S. F. (2006). Yeast network application. Gene connectivity, function, and sequence conservation: Predictions from modular yeast co-expression networks. BMC Genomics 7:40.
9. Chen, Y., Zhu, J., Lum, P. Y., Yang, X., Pinto, S., MacNeil, D. J., Zhang, C., Lamb, J., Edwards, S., Sieberts, S. K., Leonardson, A., Castellini, L. W., Wang, S., Champy, M. F., Zhang, B., Emilsson, V., Doss, S., Ghazalpour, A., Horvath, S., Drake, T. A., Lusis, A. J., Schadt, E. E. (2008). Variations in DNA elucidate molecular networks that cause disease. Nature 452:429-435.
10. D'haeseleer, P., Liang, S., Somogyi, R. (2000). Genetic network inference: from coexpression clustering to reverse engineering. Bioinformatics 16:707-726.
11. Dong, J., Horvath, S. (2007). Understanding network concepts in modules. BMC Syst. Biol. 1:24.
12. Gargalovic, P. S., Imura, M., Zhang, B., Gharavi, N. M., Clark, M. J., Pagnon, J, Yang, W. P., He, A. Q., Truong, A., Patel, S., Nelson, S. F., Horvath, S., Berliner, J. A., Kirchgessner, T. G., Lusis, A. J. (2006). Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids. Proc. Natl. Acad. Sci. USA 103(34):12741-12746.
13. Horvath, S., Zhang, B., Carlson, M., Lu, K. V., Zhu, S., Felciano, R. M., Laurance, M. F., Zhao, W., Shu, Q., Lee, Y., Scheck, A. C., Liau, L.M., Wu, H., Geschwind, D. H., Febbo, P. G., Kornblum, H. I., Cloughesy, T. F., Nelson, S. F., Mischel, P. S. (2006). Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target. Proc. Natl. Acad. Sci. USA 103(46):17402-17407.
14. Horvath, S., Dong, J. (2008). Geometric interpretation of gene coexpression network analysis. PLoS Compu. Biol. 4:8.
15. Kaufman, L., Rousseeuw, P. J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis. New York: Wiley-Interscience.
16. Langfelder, P., Horvath, S. (2007). Eigengene networks for studying the relationships between co-expression modules. BMC Syst. Biol. 1:54.
17. Li, A., Horvath, S. (2007). Network neighborhood analysis with multi-node topological overlap measure. Bioinformatics 23(2):222-231. (Pubitemid 46189613)
18. Miklos, G. L., Rubin, G. M. (1996). The role of the genome project in determining gene function: Insights from model organisms. Cell 86(4):521-529.
19. Oldham, M. C., Horvath, S., Geschwind, D. H. (2006). Conservation and evolution of gene coexpression networks in human and chimpanzee brains. Proc. Natl. Acad. Sci. USA 103:17973-17978.
20. Oldham, M. C., Konopka, G., Iwamoto, K., Langfelder, P., Kato, T., Horvath, S., Geschwind, D. H. (2008). Functional organization of the transcriptome in human brain. Nat. Neurosci. 11:1271-1282.
21. Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Francisco, CA: Morgan Kaufmann.
22. Pearl, J. (2000). Causality: Models, Reasoning, and Inference. Cambridge: Cambridge University Press.
23. Ravaz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., Barabasi, A. L. (2002). Hierarchical organization of modularity in metabolic networks. Science 297:1551-1555.
24. Schadt, E. E., Lamb, J., Yang, X., Zhu, J., Edwards, S., Guhathakurta, D., Sieberts, S. K., Monks, S., Reitman, M., Zhang, C., Lum, P.Y., Leonardson, A., Thieringer, R., Metzger, J. M., Yang, L., Castle, J., Zhu, H., Kash, S. F., Drake, T. A., Sachs, A., Lusis, A. J. (2005). An integrative genomics approach to infer causal associations between gene expression and disease. Nat. Genet. 37:710-717.
25. Spirtes, P., Glymore, C., Scheines, R., Kauffman, S., Aimale, V., Wimberly, F. (2000). Constructing Bayesian Network Models of Gene Expression Networks from Microarray Data. http://www.phil.cmu.edu/projects/genegroup/ papers/spirtes2002a.pdf
26. Storey, J. D. (2002). A direct approach to false discovery rates. J. R. Stat. Soc. B 64:479-498.
27. Storey, J. D. (2003). The positive false discovery rate: a Bayesian interpretation and the q-value. Ann. Stat. 31:2013-2035.
28. Yip, A. M., Horvath, S. (2007). Gene network interconnectedness and the generalized topological overlap measure. BMC Bioinformatics 8:22.
29. Zhang, B., Horvath, S. (2005). A general framework for weighted gene coexpression network analysis. Stat. Appl. Genet. Mol. Biol. 4:1.