yangjl / StatisticalMethodsforOmicsAssistedBreeding

Slides for short course on 'omics assisted breeding methods

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Statistical Methods for Omics Assisted Breeding

Slides for short course on 'omics assisted breeding methods.

Dates and Location Monday, November 12 to Thursday, November 15

Lecturers

  • Malachy Campbell (MC)
  • Hiroyoshi Iwata (HI)
  • Diego Jarquin (DJ)
  • Gota Morota (GM)
  • Emi Tanaka (ET)
  • Jessica Tressou (JT)

What do workshop participants expect?

What workshop participants need

  1. Their own laptop
  2. R v3.5 and RStudio XX installed
  3. Special packages need in the WS (BGLR, MTM, rrBLUP)
  4. For the R-Inla introduction: INLA, sp, fields, geoR, viridisLite + tidyverse

Participants Approximately 90 participants (50 - 70)

Day 1

  • 9:00-10:10: Basic statistical computing in R (MC) - R Markdown
  • 10:10-10:20: Break
  • 10:20-12:00: Data visualization in R (ET) - ggplot2 + desplot
  • 12:00-13:00: Lunch
  • 13:00-14:00 Introduction to Quantitative Genetics (GM)
  • 14:00-14:10: Break
  • 14:10-15:40: Least squares and Linear mixed model (MC, JT)
  • 15:40-15:50: Break
  • 15:50-16:50 Bayesian methods (JT)
  • 17:30-19:30 Social mixer

Day 2

  • 9:00-9:30 Genomic heritability (MC, GM) [PDF Slides][.Rmd]
  • 9:30-9:40 Break
  • 9:40-12:00 GWAS (HI)
  • 12:00-13:00 Lunch
  • 13:00-14:00 GBLUP and RR-BLUP (MC, GM)
  • 14:00-15:00 Bayesian alphabet (DJ)
  • 15:00-15:10 Break
  • 15:10-16:10 Classical GxE including FW, AMMI, and biplot (HI, DJ)
  • 16:10-17:10 GxE covariates (HI, DJ)

Day 3

  • 9:00-11:00 Introduction to ASReml-R (ET)
  • 11:00-11:10 Break
  • 11:10-12:00 Theoretical part of factor analytic model (ET)
  • 12:00-13:00 Lunch
  • 13:00-14:00 Application of factor analytic model to GxE analysis with ASReml (ET)
  • 14:00-14:10 Break
  • 14:10-15:10: Bayesian factor analytic model (DJ, GM)
  • 15:10-15:20: Break
  • 15:20-16:20 Spatial analysis (ET) Gilmour et al. (1997)
  • 16:20-17:00 Introduction to R-INLA (JT)

Day 4

  • 9:00-12:00 Multi-trait methods for GWAS and GP (HI, DJ, GM)
  • 12:00-13:00 Lunch
  • 13:00-15:00 Bayesian network (MC, GM) [PDF Slides][.Rmd]
  • 15:00-15:10 Break
  • 15:10-17:00 Experimental design + Optimal designs (ET)

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Slides for short course on 'omics assisted breeding methods


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