A robust pre-processing of BeadChip microarray images

• Autorzy: Kalina J.

Identyfikatory

DOI

10.1016/j.bbe.2018.04.005

• Języki publikacji: EN

Abstrakty

EN

Microarray images commonly used in gene expression studies are heavily contaminated by noise and/or outlying values (outliers). Unfortunately, standard methodology for the analysis of Illumina BeadChip microarray images turns out to be too vulnerable to data contamination by outliers. In this paper, an alternative approach to low-level pre-processing of images obtained by the BeadChip microarray technology is proposed. The novel approach robustifies the standard methodology in a complex way and thus ensures a sufficient robustness (resistance) to outliers. A gene expression data set from a cardiovascular genetic study is analyzed and the performance of the novel robust approach is compared with the standard methodology. The robust approach is able to detect and delete a larger percentage of outliers. More importantly, gene expressions are estimated more precisely. As a consequence, also the performance of a subsequently performed classification task to two groups (patients vs. control persons) is improved over the cardiovascular gene expression data set. A further improvement was obtained when considering weighted gene expression values, where the weights correspond to a robust estimate of variability of the measurements for each individual gene transcript.

Słowa kluczowe

EN

microarray image; robust image analysis; noise; outlying measurements; background effect

PL

mikromacierz; analiza obrazu; efekt tła

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2018
• Tom: Vol. 38, no. 3
• Strony: 556--563
• Opis fizyczny: Bibliogr. 30 poz., rys., tab.

Twórcy

autor

Kalina J.

• Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 2, 182 07 Praha 8, Czech Republic

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).