A novel strategy for microarray quality control using Bayesian networks

Sampsa Hautaniemi (Corresponding Author), Henrik Edgren, Petri Vesanen, Maija Wolf, Anna-Kaarina Järvinen, Olli Yli-Harja, Jaakko Astola, Olli Kallioniemi, Outi Monni

Research output: Contribution to journalArticleScientificpeer-review

40 Citations (Scopus)

Abstract

Motivation: High-throughput microarray technologies enable measurements of the expression levels of thousands of genes in parallel. However, microarray printing, hybridization and washing may create substantial variability in the quality of the data. As erroneous measurements may have a drastic impact on the results by disturbing the normalization schemes and by introducing expression patterns that lead to incorrect conclusions, it is crucial to discard low quality observations in the early phases of a microarray experiment. A typical microarray experiment consists of tens of thousands of spots on a microarray, making manual extraction of poor quality spots impossible. Thus, there is a need for a reliable and general microarray spot quality control strategy.

Results: We suggest a novel strategy for spot quality control by using Bayesian networks, which contain many appealing properties in the spot quality control context. We illustrate how a non-linear least squares based Gaussian fitting procedure can be used in order to extract features for a spot on a microarray. The features we used in this study are: spot intensity, size of the spot, roundness of the spot, alignment error, background intensity, background noise, and bleeding. We conclude that Bayesian networks are a reliable and useful model for microarray spot quality assessment.
Original languageEnglish
Pages (from-to)2031-2038
JournalBioinformatics
Volume19
Issue number16
DOIs
Publication statusPublished - 2003
MoE publication typeA1 Journal article-refereed

Fingerprint

Bayesian networks
Microarrays
Quality Control
Bayesian Networks
Microarray
Quality control
Printing
Least-Squares Analysis
Noise
Hemorrhage
Technology
Roundness
Genes
Nonlinear Least Squares
Strategy
Quality Assessment
Washing
High Throughput
Normalization
Experiment

Keywords

  • Bayesian networks
  • cDNA microarrays
  • microarray
  • data
  • quality control

Cite this

Hautaniemi, S., Edgren, H., Vesanen, P., Wolf, M., Järvinen, A-K., Yli-Harja, O., ... Monni, O. (2003). A novel strategy for microarray quality control using Bayesian networks. Bioinformatics, 19(16), 2031-2038. https://doi.org/10.1093/bioinformatics/btg275
Hautaniemi, Sampsa ; Edgren, Henrik ; Vesanen, Petri ; Wolf, Maija ; Järvinen, Anna-Kaarina ; Yli-Harja, Olli ; Astola, Jaakko ; Kallioniemi, Olli ; Monni, Outi. / A novel strategy for microarray quality control using Bayesian networks. In: Bioinformatics. 2003 ; Vol. 19, No. 16. pp. 2031-2038.
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Hautaniemi, S, Edgren, H, Vesanen, P, Wolf, M, Järvinen, A-K, Yli-Harja, O, Astola, J, Kallioniemi, O & Monni, O 2003, 'A novel strategy for microarray quality control using Bayesian networks', Bioinformatics, vol. 19, no. 16, pp. 2031-2038. https://doi.org/10.1093/bioinformatics/btg275

A novel strategy for microarray quality control using Bayesian networks. / Hautaniemi, Sampsa (Corresponding Author); Edgren, Henrik; Vesanen, Petri; Wolf, Maija; Järvinen, Anna-Kaarina; Yli-Harja, Olli; Astola, Jaakko; Kallioniemi, Olli; Monni, Outi.

In: Bioinformatics, Vol. 19, No. 16, 2003, p. 2031-2038.

Research output: Contribution to journalArticleScientificpeer-review

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T1 - A novel strategy for microarray quality control using Bayesian networks

AU - Hautaniemi, Sampsa

AU - Edgren, Henrik

AU - Vesanen, Petri

AU - Wolf, Maija

AU - Järvinen, Anna-Kaarina

AU - Yli-Harja, Olli

AU - Astola, Jaakko

AU - Kallioniemi, Olli

AU - Monni, Outi

PY - 2003

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Hautaniemi S, Edgren H, Vesanen P, Wolf M, Järvinen A-K, Yli-Harja O et al. A novel strategy for microarray quality control using Bayesian networks. Bioinformatics. 2003;19(16):2031-2038. https://doi.org/10.1093/bioinformatics/btg275