Comprehensive literature review and statistical considerations for microarray meta-analysis
Year: 2012
Type: review
Study design: Systematic Review
Abstract: With the rapid advances of various high-throughput technologies, generation of '-omics' data is commonplace in almost every biomedical field. Effective data management and analytical approaches are essential to fully decipher the biological knowledge contained in the tremendous amount of experimental data. Meta-analysis, a set of statistical tools for combining multiple studies of a related hypothesis, has become popular in genomic research. Here, we perform a systematic search from PubMed and manual collection to obtain 620 genomic meta-analysis papers, of which 333 microarray meta-analysis papers are summarized as the basis of this paper and the other 249 GWAS meta-analysis papers are discussed in the next companion paper. The review in the present paper focuses on various biological purposes of microarray meta-analysis, databases and software and related statistical procedures. Statistical considerations of such an analysis are further scrutinized and illustrated by a case study. Finally, several open questions are listed and discussed.
Source: Nucleic Acids Research
DOI: 10.1093/nar/gkr1265
Institutions: University of Pittsburgh, Pennsylvania State University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,992
Funders: University of Pittsburgh, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Mental Health, National Institute of General Medical Sciences, National Institute of Dental and Craniofacial Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: Factors Contributing to Oral Health Disparities in Appalachia, Corticolimbic Somatostatin-Related Inhibitory Dysfunction in Major Depression, Trisomy 21: Risk Factors for Chromosome Non-disjunction, Lung Genomics Research Consortium, Statistical Methods for the Analysis of Functional Genomic Data
OpenAlex ID: W1998712640
