Meta-analysis of Microarray Results: Challenges, Opportunities, and Recommendations for Standardization

Overview

Journal Gene

Specialty Molecular Biology

Date 2007 Jul 27

PMID 17651921

Citations 61

Authors

Patrick Cahan

Felicia Rovegno

Denise Mooney

John C Newman

Georges St Laurent 3rd

Timothy A McCaffrey

Affiliations

Soon will be listed here.

Abstract

Microarray profiling of gene expression is a powerful tool for discovery, but the ability to manage and compare the resulting data can be problematic. Biological, experimental, and technical variations between studies of the same phenotype/phenomena create substantial differences in results. The application of conventional meta-analysis to raw microarray data is complicated by differences in the type of microarray used, gene nomenclatures, species, and analytical methods. An alternative approach to combining multiple microarray studies is to compare the published gene lists which result from the investigators' analyses of the raw data, as implemented in Lists of Lists Annotated (LOLA: www.lola.gwu.edu) and L2L (depts.washington.edu/l2l/). The present review considers both the potential value and the limitations of databasing and enabling the comparison of results from different microarray studies. Further, a major impediment to cross-study comparisons is the absence of a standard for reporting microarray study results. We propose a reporting standard: standard microarray results template (SMART), which will facilitate the integration of microarray studies.

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References

Parkinson H, Kapushesky M, Shojatalab M, Abeygunawardena N, Coulson R, Farne A . ArrayExpress--a public database of microarray experiments and gene expression profiles. Nucleic Acids Res. 2006; 35(Database issue):D747-50. PMC: 1716725. DOI: 10.1093/nar/gkl995. View

Pan F, Chiu C, Pulapura S, Mehan M, Nunez-Iglesias J, Zhang K . Gene Aging Nexus: a web database and data mining platform for microarray data on aging. Nucleic Acids Res. 2006; 35(Database issue):D756-9. PMC: 1669755. DOI: 10.1093/nar/gkl798. View

Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C . Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet. 2001; 29(4):365-71. DOI: 10.1038/ng1201-365. View

Edgar R, Domrachev M, Lash A . Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2001; 30(1):207-10. PMC: 99122. DOI: 10.1093/nar/30.1.207. View

Ramalho-Santos M, Yoon S, Matsuzaki Y, Mulligan R, Melton D . "Stemness": transcriptional profiling of embryonic and adult stem cells. Science. 2002; 298(5593):597-600. DOI: 10.1126/science.1072530. View

Ivanova N, Dimos J, Schaniel C, Hackney J, Moore K, Lemischka I . A stem cell molecular signature. Science. 2002; 298(5593):601-4. DOI: 10.1126/science.1073823. View

Brazma A, Parkinson H, Sarkans U, Shojatalab M, Vilo J, Abeygunawardena N . ArrayExpress--a public repository for microarray gene expression data at the EBI. Nucleic Acids Res. 2003; 31(1):68-71. PMC: 165538. DOI: 10.1093/nar/gkg091. View

Tan P, Downey T, Spitznagel Jr E, Xu P, Fu D, Dimitrov D . Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 2003; 31(19):5676-84. PMC: 206463. DOI: 10.1093/nar/gkg763. View

Fortunel N, Otu H, Ng H, Chen J, Mu X, Chevassut T . Comment on " 'Stemness': transcriptional profiling of embryonic and adult stem cells" and "a stem cell molecular signature". Science. 2003; 302(5644):393. DOI: 10.1126/science.1086384. View

10.

McCarroll S, Murphy C, Zou S, Pletcher S, Chin C, Jan Y . Comparing genomic expression patterns across species identifies shared transcriptional profile in aging. Nat Genet. 2004; 36(2):197-204. DOI: 10.1038/ng1291. View

11.

Bullinger L, Dohner K, Bair E, Frohling S, Schlenk R, Tibshirani R . Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N Engl J Med. 2004; 350(16):1605-16. DOI: 10.1056/NEJMoa031046. View

12.

Valk P, Verhaak R, Beijen M, Erpelinck C, Barjesteh van Waalwijk van Doorn-Khosrovani S, Boer J . Prognostically useful gene-expression profiles in acute myeloid leukemia. N Engl J Med. 2004; 350(16):1617-28. DOI: 10.1056/NEJMoa040465. View

13.

Lu T, Pan Y, Kao S, Li C, Kohane I, Chan J . Gene regulation and DNA damage in the ageing human brain. Nature. 2004; 429(6994):883-91. DOI: 10.1038/nature02661. View

14.

Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M . KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 1998; 27(1):29-34. PMC: 148090. DOI: 10.1093/nar/27.1.29. View

15.

Wheeler D, Barrett T, Benson D, Bryant S, Canese K, Church D . Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2004; 33(Database issue):D39-45. PMC: 540016. DOI: 10.1093/nar/gki062. View

16.

Jenner R, Young R . Insights into host responses against pathogens from transcriptional profiling. Nat Rev Microbiol. 2005; 3(4):281-94. DOI: 10.1038/nrmicro1126. View

17.

Sherlock G . Of fish and chips. Nat Methods. 2005; 2(5):329-30. DOI: 10.1038/nmeth0505-329. View

18.

Larkin J, Frank B, Gavras H, Sultana R, Quackenbush J . Independence and reproducibility across microarray platforms. Nat Methods. 2005; 2(5):337-44. DOI: 10.1038/nmeth757. View

19.

Irizarry R, Warren D, Spencer F, Kim I, Biswal S, Frank B . Multiple-laboratory comparison of microarray platforms. Nat Methods. 2005; 2(5):345-50. DOI: 10.1038/nmeth756. View

20.

Bammler T, Beyer R, Bhattacharya S, Boorman G, Boyles A, Bradford B . Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods. 2005; 2(5):351-6. DOI: 10.1038/nmeth754. View