Statistical Methods for Whole Genome Analyses

This interactive book is written entirely using Jupyter notebooks.

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About ANS656

• Rohan Fernando (rohan@iastate.edu)

• Hao Cheng (haocheng@iastate.edu)

Content

• Section 1:  Basic
  • 1.1   Map Funtions
  • 1.2   Computation of Recombination Probabilities
  • 1.3   Linkage Disequilibrium
• Section 2:  Bayesian Methods
  • 2.1   Bayesian Theorem
  • 2.2   Bayesian Inference
  • 2.3   Markov Chain Monte-Carlo Methods
  • 2.4   Bayesian Inference by Application to Simple Linear Regression
  • 2.5   Extension to Multiple Linear Regression
  • 2.6   Bayesian Regression Models for Whole-Genome Analyses
• Section 3:  Single Step
  • 3.1   Single-Step GBLUP
  • 3.2   Single-Step Bayesian Regression
• Section 4:  Solutions
  • 4.1 . Bayesian Inference by Application to Simple Linear Regression
  • 4.2 . Extension to Multiple Linear Regression