Skip to main content
Log in

Comparative evaluation of microarray analysis software

  • Review
  • Published:
Molecular Biotechnology Aims and scope Submit manuscript

Abstract

A wide variety of software tools are available to analyze microarray data. To identify the optimum software for any project, it is essential to define specific and essential criteria on which to evaluate the advantages of the key features. In this review we describe the results of our comparison of several software tools. We then conclude with a discussion of the subset of tools that are most commonly used and describe the features that would constitute the “ideal microarray analysis software suite.”

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Beaucage, S. L. (2001) Strategies in the preparation of DNA oligonucleotide arrays for diagnostic applications. Curr. Med. Chem. 8, 1213–1244.

    PubMed  CAS  Google Scholar 

  2. Al-Khaldi, S. F., Martin, S. A., Rasooly, A., and Evans, J. D. (2002) DNA microarray technology used for studying foodborne pathogens and microbial habitats: minireview. J. AOAC Int. 85, 906–910.

    PubMed  CAS  Google Scholar 

  3. Marton, M. J., DeRisi, J. L., Bennett, H. A., et al. (1998) Drug target validation and identification of secondary drug target effects using DNA microarrays. Nature Med. 4, 1293–1301.

    Article  PubMed  CAS  Google Scholar 

  4. Draghici, S. (2003) Data analysis and visualization in DNA microarrays. In Introduction to Bioinformatics (Krawetz, S. and Womble, D., eds.). Humana Press, Totowa, NJ, pp. 665–692.

    Chapter  Google Scholar 

  5. Bittner, M., Meltzer, Y., Chen, Y., et al. (2000) Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 406, 536–540.

    Article  PubMed  CAS  Google Scholar 

  6. Eisen, M. B. and Brown, P. O. (1999) DNA arrays for analysis of gene expression. Methods Enzymol. 303, 179–205.

    Article  PubMed  CAS  Google Scholar 

  7. Hegde, P., Qi, R., Abernathy, K., et al. (2000) A concise guide to cDNA microarray analysis. Biotechniques 29, 548–556.

    PubMed  CAS  Google Scholar 

  8. Gentleman, R. and Carey, V. (2002) Bioconductor. R News 2, 11–16.

    Google Scholar 

  9. Saal, L., Troein, C., Vallon-Christersson, J., Gruvberger, S., Borg, A., and Peterson, C. (2002) BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data. Genome Biol. 3, software0003.1–0003.6.

    Google Scholar 

  10. Wildsmith, S. E. and Elcock, F. J. (2001) Microarrays under the microscope. Mol. Pathol. 54, 8–16.

    Article  PubMed  CAS  Google Scholar 

  11. Spellman, P. T., Miller, M., Stewart, J., et al. (2002) Design and implementation of microarray gene expression markup language (MAGE-ML). Genome Biol. 3, RESEARCH0046.

    Google Scholar 

  12. Diehn, M., Sherlock, G., Binkley G., et al. (2003) SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data. Nucleic Acids Res. 31, 219–223.

    Article  PubMed  CAS  Google Scholar 

  13. Khatri, P., Draghici, S., Ostermeier, C., and Krawetz, S. (2002) Profiling gene expression using Onto-Express. Genomics 79, 266–270.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Stephen A. Krawetz.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liu, D.K., Yao, B., Fayz, B. et al. Comparative evaluation of microarray analysis software. Mol Biotechnol 26, 225–232 (2004). https://doi.org/10.1385/MB:26:3:225

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1385/MB:26:3:225

Index Entries

Navigation