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Comparison study of microarray meta-analysis methods Campain A; Yang YHBMC Bioinformatics 2010[Aug]; 11 (ä): 408BACKGROUND: Meta-analysis methods exist for combining multiple microarray datasets. However, there are a wide range of issues associated with microarray meta-analysis and a limited ability to compare the performance of different meta-analysis methods. RESULTS: We compare eight meta-analysis methods, five existing methods, two naive methods and a novel approach (mDEDS). Comparisons are performed using simulated data and two biological case studies with varying degrees of meta-analysis complexity. The performance of meta-analysis methods is assessed via ROC curves and prediction accuracy where applicable. CONCLUSIONS: Existing meta-analysis methods vary in their ability to perform successful meta-analysis. This success is very dependent on the complexity of the data and type of analysis. Our proposed method, mDEDS, performs competitively as a meta-analysis tool even as complexity increases. Because of the varying abilities of compared meta-analysis methods, care should be taken when considering the meta-analysis method used for particular research.|*Meta-Analysis as Topic[MESH]|Algorithms[MESH]|Breast Neoplasms/genetics[MESH]|Databases, Genetic[MESH]|Female[MESH]|Gene Expression Profiling[MESH]|Humans[MESH]|Lymphoma/genetics[MESH]|Oligonucleotide Array Sequence Analysis/*methods[MESH]|ROC Curve[MESH] |
