Title :
Outlier Detection for Microarray Data
Author_Institution :
Roche Mol. Syst., Inc., Pleasanton, CA
Abstract :
It is important to estimate the impact of protocol changes on expression profiles based on microarray data and eventually on classification accuracy. This estimation should be based on experiments with replicates. Therefore, it is important to detect outliers in such experiments. This paper proposes an outlier detection algorithm for replicate microarray experiments.
Keywords :
medical signal processing; patient care; patient diagnosis; expression profiles; microarray data; outlier detection algorithm; protocol changes; replicate microarray; Bioinformatics; Costs; Detection algorithms; Error analysis; Gene expression; Humans; Probes; Protocols; RNA; Robustness;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1747-6
Electronic_ISBN :
978-1-4244-1748-3
DOI :
10.1109/ICBBE.2008.142
