Stochastic models inspired by hybridization theory for short oligonucleotide arrays

Zhijin Wu, Rafael A. Irizarry

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

High density oligonucleotide expression arrays are a widely used tool for the measurement of gene expression on a large scale. Affymetrix GeneChip arrays appear to dominate this market. These arrays use short oligonucleotides to probe for genes in an RNA sample. Due to optical noise, non-specific hybridization, probe-specific effects, and measurement error, ad-hoc measures of expression, that summarize probe intensities, can lead to imprecise and inaccurate results. Various researchers have demonstrated that expression measures based on simple statistical models can provide great improvements over the ad-hoc procedure offered by Affymetrix. Recently, physical models based on molecular hybridization theory, have been proposed as useful tools for prediction of, for example, non-specific hybridization. These physical models show great potential in terms of improving existing expression measures. In this paper we suggest that the system producing the measured intensities is too complex to be fully described with these relatively simple physical models and we propose empirically motivated stochastic models that compliment the above mentioned molecular hybridization theory to provide a comprehensive description of the data. We discuss how the proposed model can be used to obtain improved measures of expression useful for the data analysts.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual International Conference on Computational Molecular Biology, RECOMB
Pages98-106
Number of pages9
Volume8
StatePublished - 2004
EventRECOMB 2004 - Proceedings of the Eight Annual International Conference on Research in Computational Molecular Biology - San Diego, CA., United States
Duration: Mar 27 2004Mar 31 2004

Other

OtherRECOMB 2004 - Proceedings of the Eight Annual International Conference on Research in Computational Molecular Biology
CountryUnited States
CitySan Diego, CA.
Period3/27/043/31/04

Fingerprint

Oligonucleotide Probes
Oligonucleotides
Statistical Models
Stochastic models
Oligonucleotide Array Sequence Analysis
Noise
Research Personnel
RNA
Gene Expression
Genes
Measurement errors
Gene expression

Keywords

  • Affymetrix probe-level data
  • Background adjustment
  • Microarrays
  • Physical models
  • Stochastic models

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)

Cite this

Wu, Z., & Irizarry, R. A. (2004). Stochastic models inspired by hybridization theory for short oligonucleotide arrays. In Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB (Vol. 8, pp. 98-106)

Stochastic models inspired by hybridization theory for short oligonucleotide arrays. / Wu, Zhijin; Irizarry, Rafael A.

Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB. Vol. 8 2004. p. 98-106.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wu, Z & Irizarry, RA 2004, Stochastic models inspired by hybridization theory for short oligonucleotide arrays. in Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB. vol. 8, pp. 98-106, RECOMB 2004 - Proceedings of the Eight Annual International Conference on Research in Computational Molecular Biology, San Diego, CA., United States, 3/27/04.
Wu Z, Irizarry RA. Stochastic models inspired by hybridization theory for short oligonucleotide arrays. In Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB. Vol. 8. 2004. p. 98-106
Wu, Zhijin ; Irizarry, Rafael A. / Stochastic models inspired by hybridization theory for short oligonucleotide arrays. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB. Vol. 8 2004. pp. 98-106
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