Abstract:
The application of gene expression microarray technology has the potential to have a large impact in the area of oncology. There is a need to be able to identify genes associated with prolonged or reduced survival, to aid decisions regarding patient treatment and care. In addition these genes can be targeted in drug research to aid discovery and development of novel treatments. This paper uses two published Affymetrix datasets and combines the information from adenocarcinoma lung tumors to identify genes associated with survival. Kaplan-Meier survival analysis, Cox proportional hazards models and analysis of variance are used for the data analyses. The results are combined across the two datasets using Fisher’s chi-squared meta-analysis based on p-value aggregation. The false discovery rate (FDR) adjustment is made to the final pvalues.
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© 2005 Springer Science + Business Media, Inc. Boston
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Warnock, L., Stephens, R., Coleman, J. (2005). Application of Survival and Meta-analysis to Gene Expression Data Combined from Two Studies. In: Shoemaker, J.S., Lin, S.M. (eds) Methods of Microarray Data Analysis. Springer, Boston, MA. https://doi.org/10.1007/0-387-23077-7_6
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DOI: https://doi.org/10.1007/0-387-23077-7_6
Publisher Name: Springer, Boston, MA
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Online ISBN: 978-0-387-23077-1
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