摘要
Microarrayhasbecomeapopularbiotechnologyinbiologicalandmedicalresearch.However,systematicandstochasticvariabilitiesinmicroarraydataareexpectedandunavoidable,resultingintheproblemthattherawmeasurementshaveinherent"noise"withinmicroarrayexperiments.Currently,logarithmicratiosareusuallyanalyzedbyvariousclusteringmethodsdirectly,whichmayintroducebiasinterpretationinidentifyinggroupsofgenesorsamples.Inthispaper,astatisticalmethodbasedonmixedmodelapproacheswasproposedformicroarraydataclusteranalysis.TheunderlyingrationaleofthismethodistopartitiontheobservedtotalgeneexpressionlevelintovariousvariationscausedbydifferentfactorsusinganANOVAmodel,andtopredictthedifferentialeffectsofGV(genebyvariety)interactionusingtheadjustedunbiasedprediction(AUP)method.ThepredictedGVinteractioneffectscanthenbeusedastheinputsofclusteranalysis.Weillustratedtheapplicationofourmethodwithageneexpressiondatasetandelucidatedtheutilityofourapproachusinganexternalvalidation.
出版日期
2005年01月11日(中国Betway体育网页登陆平台首次上网日期,不代表论文的发表时间)