Module: Ecological Genomics (2102-510)

Persons:

• Prof. Dr. Philipp Schlüter (verantwortlich)

Degree Program:

• Biology (Master, since 01.10.2010)
  3. Semester, elective
• Promotionsstudiengang Naturwissenschaften (Doctoral degree programmes, since 14.02.2015)
  1. Semester, elective
• Promotionsstudiengang Naturwissenschaften (Doctoral degree programmes, since 14.02.2015)
  3. Semester, elective

Prerequisites for Attendance:

Proficiency in English; basic knowledge of R (or other programming/scripting skills); knowledge of basic molecular and population genetics, evolution and statistics

Sprache:

English

ECTS:

7,5 credits

Frequency:

every winter semester

Length of the Module:

4 weeks (block 2)

Module examination:

benotet

Final examination:

30% presentation | 30% short exams throughout course | 40% project report

Workload:

63 h Präsenzzeit | 162 h Eigenanteil | 225 h Arbeitsaufwand

Professional competences:

This course offers students a review of current theoretical and methodological advances in the application and analysis of genomic data for addressing evolutionary questions at the population level and at the interface of populations and species (speciation), as well as the genetic/genomic basis of phenotypes, with an emphasis on practical data analysis skills. Through lectures, paper discussions, and interactive computer labs, students will learn the advantages and limitations of specific types of genomic data and methods (e.g. from classical to NGS data) and they will be provided with an introduction to a variety of powerful software packages (and R-based approaches) for data analysis.

Key competences:

Upon completion of the course, students should be able to: (1) recognise the strengths and weaknesses of various types of genomic data; (2) perform basic analyses of genomic data using modern software packages; (3) design research studies utilising the genomics tools covered in the course.\r\nKey skills: On completion of the course, students should be able to: (1) assess the conclusions of previously published literature; (2) synthesise their knowledge through the completion of analysis projects based on previously generated data; (3) present the results of projects both in writing and orally to promote fellow students\' understanding\r\nKey transferable skills: critical/analytical thinking, English-language communication skills (writing/oral presentations), command-line/script-based (R) interaction with data.

Comments:

Criteria:
(1) suitable knowledge of pre-requisites of candidates and their confirmed ability to attend
(2) then first-come first-serve

eLearning:

Course in ILIAS

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