Methods for genomics data analysis

Krzywinski, Martin, and Naomi Altman. “Points of Significance: Comparing Samples—part I.” Nature Methods, (March 2014)

Krzywinski, Martin, and Naomi Altman. “Points of Significance: Analysis of Variance and Blocking.” Nature Methods, (July 2014)

Krzywinski, Martin, and Naomi Altman. “Points of Significance: Power and Sample Size.” Nature Methods, (November 26, 2013)

Tong, Tiejun, and Hongyu Zhao. “Practical Guidelines for Assessing Power and False Discovery Rate for a Fixed Sample Size in Microarray Experiments.” Statistics in Medicine, (May 20, 2008) - Power analysis. t-statistics, FDR types and definitions, then derivation of power calculations.

Chapter 4 “Matrix Algebra”, Chapter 5 “Linear Models”, from PH525x series - Biomedical Data Science course

ANOVA, F-test explanation 10m video

Design matrices 14m video

Jelle J. Goeman and Aldo Solari, “Multiple Hypothesis Testing in Genomics,” Statistics in Medicine, (May 20, 2014)

Statistics for Genomics: Advanced Differential Expression 24m video by Rafael Irizarry - limma statistics, Bayesian intro

Goeman, Jelle J., and Aldo Solari. “Multiple Hypothesis Testing in Genomics.” Statistics in Medicine, (May 20, 2014) - multiple testing review

Benjamini, Yoav, and Yosef Hochberg. “Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing.” Journal of the Royal Statistical Society, - FDR paper

Storey, John D., and Robert Tibshirani. “Statistical Significance for Genomewide Studies.” Proceedings of the National Academy of Sciences of the United States of America, (August 5, 2003) - q-value paper

Krzywinski, Martin, and Naomi Altman. “Points of Significance: Comparing Samples—part II.” Nature Methods, (March 28, 2014)