MISSING VALUE ESTIMATION FOR MICROARRAY EXPRESSION DATA BASED ON TOTAL LEAST SQUARES
Qiu Langbo, Gang Wang, Zhengzhi Wang · Acta Biophysica Sinica · 2005
There is missing value in microarray experiments and it will affect the stability and precision of the expression data analysis. Missing value estimating is a effective method in reducing the influence of missing values on the post-processing and there is no need for increasing experiment number. Consider the additive noise in the expression dataset, a new method based on Total Least Squares (TLS) is presented. Experimental results show that the novel method has better performance than the existing methods that have been employed.