Počet záznamů: 1
A Robust Pre-processing of BeadChip Microarray Images
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SYSNO ASEP 0489959 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název A Robust Pre-processing of BeadChip Microarray Images Tvůrce(i) Kalina, Jan (UIVT-O) RID, SAI, ORCID Zdroj.dok. Biocybernetics and Biomedical Engineering. - : Elsevier - ISSN 0208-5216
Roč. 38, č. 3 (2018), s. 556-563Poč.str. 8 s. Jazyk dok. eng - angličtina Země vyd. PL - Polsko Klíč. slova Microarray ; Robust image analysis ; Noise ; Outlying measurements ; Background effect Vědní obor RIV IN - Informatika Obor OECD Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Institucionální podpora UIVT-O - RVO:67985807 UT WOS 000442914100011 EID SCOPUS 85046878739 DOI 10.1016/j.bbe.2018.04.005 Anotace 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. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2019
Počet záznamů: 1