Journal
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
Volume 4, Issue 4, Pages 357-376Publisher
INDERSCIENCE ENTERPRISES LTD
DOI: 10.1504/IJDMB.2010.034194
Keywords
gene function prediction; microarray data analysis; Pearson correlation coefficient; meta-analysis; meta correlation; p-value
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Funding
- National Science Foundation [NSF/ITRIIS-0407204]
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Tremendous amounts of microarray data for various organisms have provided a rich opportunity for computational analyses of gene products. Integrating these data can help inferring biological knowledge effectively. We present a new statistical method of integrating multiple microarray datasets for gene function prediction. We tested the performance of our model using yeast and human datasets. Our results show that combining multiple datasets improves the accuracy over the best function prediction of any single dataset significantly. We also compared performance of the meta p-value and meta correlation methods for function prediction. Supplementary results and code are available at http://digbio.missouri.edu/meta_analyses.
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