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On the Robustness of Algorithms for Clustering of Gene Expression Data
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.
2003 (English)Report (Other academic)
Abstract [en]

The progress in microarray technology is evident and huge amounts of gene expression data are currently being produced. A complicating matter is that there are various sources of uncertainty in microarray experiments, as well as in the analysis of expression data. This problem has generated an increased interest in the validation of methods for analysis of expression data. Clustering algorithms have been found particularly useful for the study of coexpressed genes, and this paper therefore concerns the robustness of partitional clustering algorithms. These algorithms use a predefined number of clusters and assign each gene to exactly one cluster. The effect of repeated clustering using identical algorithm parameters and input data is investigated for the self-organizing map (SOM) and the $k$-means algorithm. The susceptibility to measurement noise is also studied. A reproducibility measure is proposed and used to assess the results from the performed clustering experiments. Well-known publicly available datasets are used. Results show that clusterings are not necessarily reproducible even when identical algorithm parameters are used, and that the problems are aggravated when measurement noise is introduced.

Place, publisher, year, edition, pages
Skövde: Institutionen för kommunikation och information , 2003. , 10 p.
Series
IKI Technical Reports, HS-IDA-TR-03-004
National Category
Information Science
Identifiers
URN: urn:nbn:se:his:diva-1248OAI: oai:DiVA.org:his-1248DiVA: diva2:2382
Available from: 2008-06-17 Created: 2008-06-17 Last updated: 2010-04-08

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fulltext(213 kB)405 downloads
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Gamalielson, JonasOlsson, Björn
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf