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FMSN01/MASM20: Statistics in Genetics,
7.5 ECTS credits

Current information Autumn 2009:

The course is unfortunately cancelled! Any student intending to take the course is welcome to take the course MASM21 Analysis of Survival data instead. Analysis of Survival Data starts Monday november 2, at 10:15-12.00 in MH:227. Analysis of Survival Data may be included in Biological and Medical Modelling on Engineering Mathematics instead of Statistics in Genetics.

Obsolete information Autumn 2007:


Linda Hartman, tel 046-222 47 79, linda@maths.lth.se, MH:138A.


A basic course in mathematical statistics and an additional course in stochastic processes. Conditional probabilities are improtant for the course.

Course contents:

The course covers methods for using statistical methods in gene mapping for human hereditary diseases, i.e. localising corresponding chromosome positions in the human genome. Initially, an introduction to statistical genetics is presented, including genetical definitions. Secondly, theory and methodology within the fields of parametric- and nonparametric linkage analysis and association analysis are discussed.

The course is a är "sistercourse" to BNF073: Statistics in Genetics at the Bioinformatics Master programme.

Course schedule:

The course schedule (preliminary version) [pdf][ps]

General information:

A pigeon-hole for the course is located on the first floor of Matematikhuset, entrance Mathematical statistics, just to the right above the stairs. Mathematical statistics has a notice-board at the ground floor, left of the entrances in the lobby.


Home exam, compulsory computer exercises, and oral project presentation. The course grade is based 90% on the home exam and 10% on the project presentation.

Computer laboration/Project:

Compulsory moments: Attend and participate in the final seminar where the course participants presents their individual projects (carried out in groups od two students)

For the linkage lab, we use the analysis program GENEHUNTER, and for association analysis we use Haploview.


The course instruction is through cooperative learning.