In charlotte-ngs/lbgfs2020: Livestock Breeding and Genomics (Fall 2020)

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

Welcome to the website of

751-6305-00L Livestock Breeding and Genomics

Topics for Master Theses

Topics for Master Theses at Qualitas AG together with ETH are available from here.

Description

Methods for analysing livestock data, in particular for the estimation of breeding values: principles of selection index, introduction to BLUP, application of common models used, relationship matrix, methods for the estimation of variance components, basics of breeding programs. The material will be illustrated via exercises and assignments.

Information

Lecturer: Peter von Rohr
Date: Friday 9-12
Room: LFW C 11
Exam:
- Time: 09:15 - 11:15
- Room: LFW C 11

Exercise Platform

The exercise platform is available under: http://2-htz.quagzws.com:<PORT> where <PORT> must be replaced by the number that you received by E-Mail. The username is 'rstudio' and the password is also in the E-Mail.

Questions

Questions can be asked during the lecture and during the exercise hour or via e-mail:

Peter von Rohr (peter.vonrohr at usys.ethz.ch)

### # header names of tables
vecTableHeaders <- c("Week", "Date", "Topic")

Lecture Program

# define course start date
dCourseStart <- as.Date("2020/09/18")
# set number of weeks in semester
nNrSemesterWeeks <- 14
# define columns for weaks, dates, and subjects
Week <- 1:nNrSemesterWeeks
Date <- format(seq(dCourseStart, by = "week", length.out = nNrSemesterWeeks), "%d.%m")
Topic <- vector(mode = "character", length = nNrSemesterWeeks)
# subjects per week
Topic[1] <- "Introduction to Livestock Breeding and Genomics"
Topic[2] <- "Review of Quantitative Genetics/Single Locus"
Topic[3] <- "Genetic Evaluation with Different Sources of Information"
Topic[4] <- "Genetic Covariance Between Relatives"
Topic[5] <- "Best Linear Unbiased Prediction (BLUP) - Univariate Analysis"
Topic[6] <- "BLUP - Additional Aspects"
Topic[7] <- "BLUP - Multiple Traits"
Topic[8] <- "Variance and Inbreeding"
Topic[9] <- "Variance Components Estimation"
Topic[10] <- "Genomic Selection"
Topic[11] <- "Genom-Wide Association Studies"
Topic[12] <- "Review on Selection Index Theory"
Topic[13] <- "Questions, Test Exam"
Topic[14] <- "Exam"

dfCnTable <- data.frame(Week, Date, Topic, stringsAsFactors = FALSE)
colnames(dfCnTable) <- vecTableHeaders
knitr::kable(dfCnTable)