BIN300 Statistical Genomics
There may be changes to the course due to to corona restrictions. See Canvas and StudentWeb for info.
Showing course contents for the educational year 2021 - 2022 .
Course responsible: Theodorus Hendrikus Elisabeth Meuwissen
Teachers: Mallikarjuna Rao Kovi
ECTS credits: 10
Faculty: Faculty of Biosciences
Teaching language: EN
Teaching exam periods:
This course starts in Spring parallel. This course has teaching/evaluation in Spring parallel.
Course frequency: Annually
First time: 2004V
- Mapping of single genes and markers, - Mapping of Quantitative Trait Loci (QTL), - Fine scale mapping of QTL based on linkage disequilibrium, - Marker assisted selection, - Genomic selection.
Students can describe: (i) alternative methods and experimental designs for the mapping of genes and QTL, (ii) alternative methods for the genomic prediction of genetic values of individuals, (iii) alternative methods for the analysis of (RNA) sequence data.
Students can (fine-scale) map genes and QTL, predict genomic breeding values, and analyse (RNA) sequence data.
The students should develop analytical approaches to statistical designs for QTL mapping, gene expression data analyses, and genomic data analyses. The students should acquire sufficient knowledge to recognize the mechanics of softwares developed for the afore mentioned analyses, and be able to follow more advanced courses in these fields.
Lectures and practical computer exercises. Computer-supported learning is used during the computer exercises.
The student's learning is supported through tutoring, practical exercises, and plenary discussions.
The course is based upon lecture notes.
All independent assignments.
Final oral examination. Grading A-F
Special requirements in Science
Reduction of credits:
Type of course:
An external examiner is used to ensure the quality of the examination and that the quality of the course remains at a sufficiently high level.
Examination details: Oral exam: A - E / F