Complementary hierarchical clustering.

@article{Nowak2008ComplementaryHC,
  title={Complementary hierarchical clustering.},
  author={Gen Nowak and Robert Tibshirani},
  journal={Biostatistics},
  year={2008},
  volume={9 3},
  pages={467-83}
}
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, the clustering patterns generated by most algorithms tend to be dominated by groups of highly differentially expressed genes that have closely related expression patterns. Sometimes, these genes may not be relevant to the biological process under study or their functions may already be known. The problem is that these genes can potentially drown out the effects of other genes that are relevant or… CONTINUE READING

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References

Publications referenced by this paper.
Showing 1-10 of 19 references

Spectral clustering and its use in bioinformatics

Desmond J. Highama, Gabriela Kalnaa, Milla Kibbleb
2007

Biclustering algorithms for biological data analysis: a survey

IEEE/ACM Transactions on Computational Biology and Bioinformatics • 2004
View 1 Excerpt

GEISLER, S.and others(2003). Repeated observation of breast tumor subtypes in independent gene expression data sets

T. ii196–ii205. SØRLIE, R. TIBSHIRANI, +6 authors R. PESICH
2003

Repeated observation of breast tumor subtypes in independent gene expression data sets.

Proceedings of the National Academy of Sciences of the United States of America • 2003

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