Microarray data mining is achieved by multivariate statistics based on SAS

Multivariate statistics using SAS is applied to mine a dataset from GEO.Expression data of fourteen nuclear receptors in a lung cancer microarray experiment is analyzed by non-parameter test,discriminant analysis and regression analysis.As a result,ER1,VDR,RARα and RORα is differentially expressed between adenocarcinoma and squamous cell carcinoma under significance of 0.05;RARβ is differentially expressed between recurrent and non-recurrent cancer;discriminant analysis shows VDR and RORα together can predict pathotype,and RARβ and PPARα together can discriminate recurrence;the false-rate is 0.2389 and 0.3457,respectively.Logistic regression is established to predict pathotype and variables included are also VDR and RORα,with OR at 0.126 and 4.452,respectively.Therefore,multivariate statistics based on SAS is a potential way to mine microarray data and conclusions based on SAS integration of different microarray experiments might be helpful for establishing hypothesis once microarray experiments can be standardized.