BIOINF 704 Statistical Bioinformatics

Below description edited in year: 2011

Points: 15

Prereqs: No knowledge of basic biology will be assumed in this course, and the required concepts will be taught as part of the class. Familiarity with linear models (STATS 330) and statistical theory (STATS 310) is expected, although a brief overview of the fundamentalsof each area will be given. Experience with statistical softwaresuch as S-plus, R or Matlab is also required, and students may findtaking STATS 782 in semester 1 an advantage.

Restrictions: Stats 771

Credit: Final exam 40%, Assignments 40%, Mid-semester test 20%

Taught: Second Semester City

Website: BIOINF 704 website

BIOINF 704 provides (1) a detailed overview of the statistical techniques required to analyse modern human genetic data (~70%) and (2) an introduction to the analysis of gene-expression data (~30%). The methods used to locate genomic regions involved in debilitating genetic diseases through the analysis of pedigree data are introduced. Central concepts in population genetics are also presented and a thorough description of genome-wide association studies (GWAS) is given. In particular, BIOSCI 744 puts the emphasis on the statistical tools that are used to detect associations between specific diseases and genomic variants in human populations. The limitations and Ethical implications of GWAS are also discussed. The second part of the course focuses on the statistical analysis of microarray data and the methods that are used to make sense of the expression levels of thousands of genes measured in various experimental conditions. BIOINF 704 is mainly aimed at statisticians, medical school students and biologists with a desire to understand the challenges brought by the wealth of genetic data available nowadays. It will provide them with the statistical techniques required to make sense of this type of data. No knowledge of basic biology will be assumed in this course, and the required concepts will be taught as part of the class. Experience with statistical softwares such as S-plus, R or Matlab is also a plus.

Disclaimer:
Although every reasonable effort is made to ensure accuracy, this information for the course year (2012), is provided as a general guide only for students and is subject to alteration. All students enrolling at the University of Auckland must consult its official document, the University of Auckland Calendar, to ensure that they are aware of and comply with all regulations, requirements and policies.