A Robust Pre-processing of BeadChip Microarray Images

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F18%3A00489959" target="_blank" >RIV/67985807:_____/18:00489959 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.bbe.2018.04.005" target="_blank" >http://dx.doi.org/10.1016/j.bbe.2018.04.005</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.bbe.2018.04.005" target="_blank" >10.1016/j.bbe.2018.04.005</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Robust Pre-processing of BeadChip Microarray Images

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

A Robust Pre-processing of BeadChip Microarray Images

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Biocybernetics and Biomedical Engineering

ISSN

0208-5216

e-ISSN

—

Svazek periodika

38

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

8

Strana od-do

556-563

Kód UT WoS článku

000442914100011

EID výsledku v databázi Scopus

2-s2.0-85046878739