TY - GEN
T1 - Contamination removal methods in cDNA microarray data
AU - Chan, Shih Huang
AU - Chang, Wan Chi
AU - Lin, Chien Ju
PY - 2006
Y1 - 2006
N2 - Our objective is to detect and remedy the contaminated spots for cDNA microarray data. To check the existence of unusual spots, single linkage clustering is used to assess the background intensities. Then, K-means clustering method is applied to identify the contaminated area. We estimate the amount of contamination, for background and foreground, through the use of nonparametric spline regression and empirical cumulative distribution approach, separately. A simulation study shows that the performance of the recommended approach is promising.
AB - Our objective is to detect and remedy the contaminated spots for cDNA microarray data. To check the existence of unusual spots, single linkage clustering is used to assess the background intensities. Then, K-means clustering method is applied to identify the contaminated area. We estimate the amount of contamination, for background and foreground, through the use of nonparametric spline regression and empirical cumulative distribution approach, separately. A simulation study shows that the performance of the recommended approach is promising.
UR - http://www.scopus.com/inward/record.url?scp=48649109196&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48649109196&partnerID=8YFLogxK
U2 - 10.1109/GENSIPS.2006.353145
DO - 10.1109/GENSIPS.2006.353145
M3 - Conference contribution
AN - SCOPUS:48649109196
SN - 1424403855
SN - 9781424403851
T3 - 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006
SP - 39
EP - 40
BT - 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006
T2 - 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006
Y2 - 28 May 2006 through 30 May 2006
ER -