title: Introduction to BLUPF90 suite programs author: Yutaka Masuda date: September 2019 subject: "Introduction to BLUPF90 suite programs" tags: [introduction,tutorial] ...
- Short introduction to BLUPF90 programs
- Differences with other software
- About the software
- About this tutorial
- Introduction
- Availability
- Running a program in Windows
- Running a program in Linux and MacOS X
- Additional settings
- Setup a text editor
- Introduction
- Trivial analyses for fixed models
- Trivial analyses for mixed models
- Trivial analyses for single-step GBLUP
- Trivial analyses for multiple-trait models
- 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?
- Restricted (residual) maximum likelihood with AIREMLF90
- Gibbs sampling and post-Gibbs analysis
- Advanced usage of AIREMLF90
- Advanced features for Gibbs sampling programs
- Introduction
- Chapter 3. Example 3.1 Animal model
- Chapter 3. Example 3.2. Sire model
- Chapter 3. Example 3.3. Reduced animal model
- Chapter 3. Example 3.4 Animal model with groups
- Chapter 4. Example 4.1 Repeatability model
- Chapter 4. Example 4.2. Model with common environmental effects
- Chapter 5. Example 5.1. Multiple-trait model, Equal design matrices and no missing records
- Chapter 5. Example 5.2. Multiple-trait model, Equal design matrices with missing records
- Chapter 5. Example 5.3. Multiple-trait model, Unequal design matrices
- Chapter 5. Example 5.4. Multivariate models with no environmental covariance
- Chapter 7. Example 7.1. Animal model for a maternal trait
- Chapter 8. Example 8.1. Animal model with social interaction effects
- Chapter 9. Example 9.1. Fixed regression model
- Chapter 9. Example 9.2. Random regression model
- Chapter 10. Example 10.2. Prediction of breeding values with marker information
- Chapter 10. Example 10.3. Directly predicting the additive genetic merit at the QTL
- 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 11.5. Mixed linear models with polygenic effects
- Chapter 11. Example 11.6. Single-step approach
- Chapter 12. Example 12.1. Animal model with dominance effect
- Chapter 12. Example 12.3. Method for rapid inversion of the dominance matrix
- Chapter 13. Example 13.1. The threshold model
- Chapter 13. Example 13.2. Joint analysis of quantitative and binary traits
- 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