MOTIVATION: Detailed comparison and analysis of the output of DNA gene expression arrays from multiple samples require global normalization of the measured individual gene intensities from the different hybridizations. This is needed for accounting for variations in array preparation and sample hybridization conditions. RESULTS: Here, we present a simple, robust and accurate procedure for the global normalization of datasets generated with single-channel DNA arrays based on principal component analysis. The procedure makes minimal assumptions about the data and performs well in cases where other standard procedures produced biased estimates. It is also insensitive to data transformation, filtering (thresholding) and pre-screening.
MOTIVATION: Detailed comparison and analysis of the output of DNA gene expression arrays from multiple samples require global normalization of the measured individual gene intensities from the different hybridizations. This is needed for accounting for variations in array preparation and sample hybridization conditions. RESULTS: Here, we present a simple, robust and accurate procedure for the global normalization of datasets generated with single-channel DNA arrays based on principal component analysis. The procedure makes minimal assumptions about the data and performs well in cases where other standard procedures produced biased estimates. It is also insensitive to data transformation, filtering (thresholding) and pre-screening.
Authors: Radka Stoyanova; Kris Huang; Kiri Sandler; Hyungjoon Cho; Sean Carlin; Pat B Zanzonico; Jason A Koutcher; Ellen Ackerstaff Journal: Transl Oncol Date: 2012-12-01 Impact factor: 4.243
Authors: Christopher R Cabanski; Yuan Qi; Xiaoying Yin; Eric Bair; Michele C Hayward; Cheng Fan; Jianying Li; Matthew D Wilkerson; J S Marron; Charles M Perou; D Neil Hayes Journal: PLoS One Date: 2010-03-26 Impact factor: 3.240
Authors: Derrick K Rollins; Dongmei Zhai; Alrica L Joe; Jack W Guidarelli; Abhishek Murarka; Ramon Gonzalez Journal: BMC Bioinformatics Date: 2006-08-14 Impact factor: 3.169