About this course

- 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.

Learning outcome

Knowledge:

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.

Skills:

Students can (fine-scale) map genes and QTL, predict genomic breeding values, and analyse (RNA) sequence data.

General capabilities:

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.

  • Learning activities

    Lectures and practical computer exercises. Computer-supported learning is used during the computer exercises.

  • Teaching support

    The student's learning is supported through tutoring, practical exercises, and plenary discussions.

  • Syllabus

    The course is based upon lecture notes.

  • Prerequisites

    STAT200.

  • Assessment method

    Final oral examination. Grading A-F. Practicals need to be submitted on Canvas before exam results are given.

    Oral exam Karakterregel: Letter grades

  • About use of AI

  • Examiner scheme

    An examiner is used to ensure the quality of the examination and that the quality of the course remains at a sufficiently high level.

  • Mandatory activity

    All independent assignments need to be submitted on Canvas.

  • Teaching hours

    52 hours.

  • Admission requirements

    Special requirements in Science