Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Primer
  • Published:

How does gene expression clustering work?

Clustering is often one of the first steps in gene expression analysis. How do clustering algorithms work, which ones should we use and what can we expect from them?

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: A simple clustering example with 40 genes measured under two different conditions.

Bob Crimi

References

  1. Tavazoie, S., Hughes, J.D., Campbell, M.J., Cho, R.J. & Church, G.M. Systematic determination of genetic network architecture. Nat. Genet. 22, 281–285 (1999).

    Article  CAS  Google Scholar 

  2. Jain, A.K. & Dubes, R.C. Algorithms for Clustering Data. (Prentice Hall, Englewood Cliffs, New Jersey, 1988).

    Google Scholar 

  3. Aldenderfer, M.S. & Blashfield, R.K. Cluster Analysis. (Sage Publication, Newbury Park, California, 1984).

  4. Jiang, D., Tang, C. & Zhang, A. Cluster analysis for gene expression data: a survey. IEEE Trans. Know. Data Eng. 16, 1370–1386 (2004).

    Article  Google Scholar 

  5. Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863–14868 (1998).

    Article  CAS  Google Scholar 

  6. Tamayo, P. et al. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc. Natl. Acad. Sci. USA 96, 2907−2912 (1999).

  7. Handl, J., Knowles, J. & Kell, D.B. Computational cluster validation in post-genomic data analysis. Bioinformatics 21, 3201–3212 (2005).

    Article  CAS  Google Scholar 

  8. Gibbons, F.D. & Roth, F.P. Judging the quality of gene expression-based clustering methods using gene annotation. Genome Res. 12, 1574–1581 (2002).

    Article  CAS  Google Scholar 

  9. Costa, I.G., de Carvalho, F.A. & de Souto, M.C. Comparative analysis of clustering methods for gene expression time course data. Genet. Mol. Biol. 27, 623–631 (2004).

    Article  CAS  Google Scholar 

  10. Datta, S. & Datta, S. Comparisons and validation of statistical clustering techniques for microarray gene expression data. Bioinformatics 19, 459–466 (2003).

    Article  CAS  Google Scholar 

  11. Gat-Viks, I., Sharan, R. & Shamir, R. Scoring clustering solutions by their biological relevance. Bioinformatics 19, 2381–2389 (2003).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

D'haeseleer, P. How does gene expression clustering work?. Nat Biotechnol 23, 1499–1501 (2005). https://doi.org/10.1038/nbt1205-1499

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt1205-1499

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing