A model for measurement error for gene expression arrays.
We introduce a model for measurement error in gene expression arrays as a function of the expression level. This model, together with analysis methods, data transformations, and weighting, allows much more precise comparisons of gene expression, and provides guidance for analysis of background, determination of confidence intervals, and preprocessing data for multivariate analysis.
Rocke
D M
DM
Department of Applied Science, University of California-Davis, 3011 Engineering Unit III, Davis, CA 95616, USA.
Durbin
B
B
D019295:Computational Biology; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D015233:Models, Statistical; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data