目錄Microarray Data Analysis Lecture 2. Statistical significance and data filtering A brief history of statistical testing The Basics of Hypothesis Testing One Way ANOVA F-test, Splus>summary(aov(X~T,DF)) The problem of multiple-testing Ex. i.i.d. uniform distribution of p-values on (0,1) Bonferroni and Sidak corrections (“Single-step”) Comparison of Bonferroni and Sidak Adjusted p-Values Resampling-based (Computationally Intensive*) Methods I. Permutation Test II. Bootstrap Estimation and Hypothesis Testing (“Sampling with replacement”, Efron 1982, Jackknife, etc.) The Bootstrap t-test Step-Down Methods Can Be More Powerful: Westfall&Young (1993) Step-Down t-Tests Step-Down Permutation Tests Comparison with single-slide methods Significance analysis of microarrays (SAM) and false discovery rate (FDR) Comparisons with SAM Literature, software and websites |
作者:Michael Zhang
電子郵件: mzhang@cshl.org 首頁: http://argon.cshl.org/mzhang/cv.html 若需最佳效果，請使用 |
