Robust estimators for expression analysis.
BACKGROUND
We consider the problem of estimating values associated with gene expression from oligonucleotide arrays. Such estimates should linearly track concentration, yield non-negative results, have statistical guarantees of robustness against outliers, and allow estimates of significance and variance.


RESULTS
A hierarchy of simple models is used to design robust estimators meeting these goals for both stand alone and comparative experiments. This algorithm has been validated against an extensive panel of known spike experiments, and shows comparable performance to existing standards.
Hubbell
Earl
E
Affymetrix, 3380 Central Expressway, Santa Clara, CA 95051, USA. earl_hubbell@affymetrix.com
Liu
Wei-Min
WM
Mei
Rui
R
D000465:Algorithms; D015342:DNA Probes; D015870:Gene Expression / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011786:Quality Control; D012333:RNA, Messenger / Q000235:genetics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D015003:Yeasts / Q000235:genetics
D015342:DNA Probes; D012333:RNA, Messenger