Cross-Platform Microarray Data Integration Combining Meta-Analysis and Gene Set Enrichment Analysis
نویسندگان
چکیده
Integrative analysis of microarray data has been proven as a more reliable approach to deciphering molecular mechanisms underlying biological studies. Traditional integration such as meta-analysis is usually gene-centered. Recently, gene set enrichment analysis (GSEA) has been widely applied to bring gene-level interpretation to pathway-level. GSEA is an algorithm focusing on whether an a priori defined set of genes shows statistically significant differences between two biological states. However, GSEA does not support integrating multiple microarray datasets generated from different studies. To overcome this, the improved version of GSEA, ASSESS, is more applicable, after necessary modifications. By making proper combined use of meta-analysis, GSEA, and modified ASSESS, this chapter reports two workflow pipelines to extract consistent expression pattern change at pathway-level, from multiple microarray
منابع مشابه
Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery
The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually...
متن کاملMeta-analysis for pathway enrichment analysis when combining multiple genomic studies
MOTIVATION Many pathway analysis (or gene set enrichment analysis) methods have been developed to identify enriched pathways under different biological states within a genomic study. As more and more microarray datasets accumulate, meta-analysis methods have also been developed to integrate information among multiple studies. Currently, most meta-analysis methods for combining genomic studies f...
متن کاملA powerful Bayesian meta-analysis method to integrate multiple gene set enrichment studies
MOTIVATION Much research effort has been devoted to the identification of enriched gene sets for microarray experiments. However, identified gene sets are often found to be inconsistent among independent studies. This is probably owing to the noisy data of microarray experiments coupled with small sample sizes of individual studies. Therefore, combining information from multiple studies is like...
متن کاملMeta-Analysis of Pathway Enrichment: Combining Independent and Dependent Omics Data Sets
A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion f...
متن کاملExtracellular exosomes and preeclampsia: a microarray-based study and functional enrichment analysis
Background: Preeclampsia (PE) is a heterogeneous pregnancy disease which the exact pathophysiology of it is unknown. Recently exosomes have been indicated as a causative factor in the pathogenesis of PE. The aim of the study was to investigate in microarray library data to extract the differentially expressed genes (DEGs) in PE and to perform a functional enrichment analysis to predict the rol...
متن کامل