A novel strategy for microarray quality control using Bayesian networks.
BACKGROUND
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.


BACKGROUND
http://sigwww.cs.tut.fi/TICSP/SpotQuality/.
Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland. sampsa.hautaniemi@tut.fi
Sampsa
S
Hautaniemi
Henrik
H
Edgren
Petri
P
Vesanen
Maija
M
Wolf
Anna-Kaarina
AK
Järvinen
Olli
O
Yli-Harja
Jaakko
J
Astola
Olli
O
Kallioniemi
Outi
O
Monni
D000465:Algorithms; D001483:Base Sequence; D001499:Bayes Theorem; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D016011:Normal Distribution; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods*