Title :
Correction of copy number variation data using principal component analysis
Author :
Chen, Jiayu ; Liu, Jingyu ; Calhoun, Vince D.
Author_Institution :
Dept. of Electr. Eng., Univ. of New Mexico, Albuquerque, NM, USA
Abstract :
Copy number variation (CNV) detection using SNP array data is challenging due to the low signal-to-noise ratio. In this study, we propose a principal component analysis (PCA) based correction to eliminate variance in CNV data induced by potential confounding factors. Simulations show a substantial improvement in CNV detection accuracy after correction. We also observe a significant improvement in data quality in real SNP array data after correction.
Keywords :
DNA; bioinformatics; data analysis; molecular biophysics; principal component analysis; CNV detection accuracy; SNP array data; copy number variation data correction; data quality; principal component analysis; signal-to-noise ratio; Log R Ratio; copy number variation; principal component analysis;
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on
Conference_Location :
Hong, Kong
Print_ISBN :
978-1-4244-8303-7
Electronic_ISBN :
978-1-4244-8304-4
DOI :
10.1109/BIBMW.2010.5703928
