Introduction to BLUPF90 suite programs

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Revision History

• Revision History

Acknowledgment

• Acknowledgment

License

• License

Introduction

• Short introduction to BLUPF90 programs
• Differences with other software
• About the software
• About this tutorial
• New programs

Download and Installation

• Introduction
• Availability
• Running a program in Windows
• Running a program in Linux and MacOS X
• Additional settings
• Setup a text editor

Quick tour of BLUPF90

• Introduction
• Trivial analyses for fixed models
• Trivial analyses for mixed models
• Trivial analyses for single-step GBLUP
• Trivial analyses for multiple-trait models

Data preparation with RENUMF90

• Introduction
• Basic data preparation
• Animal model with pedigree file
• Genomic model with SNP-marker file
• Multiple-trait models
• Advanced usage of RENUMF90
• What if I don’t want to use RENUMF90?

Variance component estimation

• Restricted (residual) maximum likelihood with AIREMLF90 (BLUPF90+)
• Gibbs sampling and post-Gibbs analysis
• Advanced usage of AIREMLF90 (BLUPF90+)
• Advanced features for Gibbs sampling programs

Practical genomic analysis

• Introduction
• Overview of genomic features
• Files used in genomic analysis
• Quality control of SNP markers
• Tuning and input/output of relationship matrices
• Fine control of single-step GBLUP
• Performing GBLUP
• GWAS using the ssGBLUP framework

Numerical examples from Mrode and Pocrnic (2023)

• Introduction
• Chapter 4. Example 4.1. Animal model
• Chapter 4. Example 4.2. Sire model
• Chapter 4. Example 4.3. Reduced animal model
• Chapter 4. Example 4.4. Animal model with groups
• Chapter 5. Example 5.1. Repeatability model
• Chapter 5. Example 5.2. Model with common environmental effects
• Chapter 6. Example 6.1. Multiple-trait model, Equal design matrices and no missing records
• Chapter 6. Example 6.2. Multiple-trait model, Equal design matrices with missing records
• Chapter 6. Example 6.3. Multiple-trait model, Unequal design matrices
• Chapter 6. Example 6.4. Multivariate models with no environmental covariance
• Chapter 7. Example 7.1. Canonical transformation
• Chapter 7. Example 7.2. Cholesky transformation
• Chapter 8. Example 8.1. Animal model for maternal traits
• Chapter 8. Example 8.2. Reduced animal model with maternal effects
• Chapter 9. Example 9.1. Animal model with social interaction effects
• Chapter 10. Example 10.1. Fixed regression model
• Chapter 10. Example 10.2. Random regression model
• Chapter 11. Example 11.1. Fixed effect model for SNP effects
• Chapter 11. Example 11.2. Mixed linear model for computing SNP effects
• Chapter 11. Example 11.3. Equivalent models: GBLUP
• Chapter 11. Example 11.4. SNP solutions from GBLUP
• Chapter 11. Example 11.6. Base-population allele frequency
• Chapter 11. Example 11.7. Mixed linear models with polygenic effects
• Chapter 11. Example 11.8. Haplotype models
• Chapter 11. Example 11.13. Multivariate genomic models
• Chapter 12. Example 12.1. Single-step approaches: basic principle
• Chapter 12. Example 12.2. APY approach
• Chapter 13. Example 13.1. Animal model with dominance effect
• Chapter 13. Example 13.2. Total genetic merit
• Chapter 13. Example 13.3. Genomic models for dominance effects
• Chapter 13. Example 13.4. Inclusion of genomic inbreeding
• Chapter 13. Example 13.5. Epistatis
• Chapter 15. Example 15.1. The threshold model
• Chapter 15. Example 15.2. Joint analysis of quantitative and binary traits

Large-scale genetic evaluation

• Introduction
• Issues in a large scale analysis
• Iteration on data with preconditioned conjugate gradient (PCG)
• Approximation of accuracy and reliability
• REML estimation with large data

References

• References

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