论文信息 - Modifying Microarray Analysis Methods for Categorical Data - SAM and PAM for SNPs

Modifying Microarray Analysis Methods for Categorical Data - SAM and PAM for SNPs

Common and important tasks arising in microarray experiments are the identification of differentially expressed genes and the classification of biological samples. The SAM (Significance Analysis of Microarrays) procedure is a widely used method for dealing with the multiple testing problem concerned with the former task, whereas the PAM (Prediction Analysis of Microarrays) procedure is a method that can cope with the problems associated with the latter task.

Holger Schwender | H. Schwender

[1] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[2] R. Tibshirani,et al. Diagnosis of multiple cancer types by shrunken centroids of gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[3] John D. Storey. The positive false discovery rate: a Bayesian interpretation and the q-value , 2003 .

[4] Ross Ihaka,et al. Gentleman R: R: A language for data analysis and graphics , 1996 .

[5] John D. Storey,et al. Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[6] R. Tibshirani,et al. Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[7] Holger Schwender,et al. Comparison of the empirical bayes and the significance analysis of microarrays , 2003 .