- Docente: Rita Casadio
- Credits: 6
- SSD: BIO/18
- Language: English
- Moduli: Rita Casadio (Modulo 1) Osman Ugur Sezerman (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Bioinformatics (cod. 8020)
Learning outcomes
At the end of the course, the student has knowledge of the main approaches for genetic data analysis, with an emphasis on the human genome, genetic mapping and disease gene identification strategies. In particular, the student is able to: understand the structure of genetic variability and its phenotypic effects, browse human genome data, apply methods to map and identify disease genes, use some current software for genetic data analysis, correctly interpret results, choose the best strategy to design a genetic study.
Course contents
Analysis of the human genome and genetic variation, mutations and polymorphisms, genetic markers, copy number variants.
Browsing genome data: the UCSC Genome
Browser
Linkage analysis: parametric and non-parametric methods. Strategies
for mapping genes involved in mendelian and complex
disorders.
Association analysis: Linkage disequilibrium mapping, genome wide
association studies, the HapMap project, SNP selection and tag
SNPs.
Introduction to next generation sequencing
technologies.
Computer practical exercises using some freely available genetic
analysis software.
Readings/Bibliography
Selected papers
Suggested book: Strachan T., Read A.P. Human Molecular Genetics (4th edition)
Assessment methods
Written and/or oral test
Teaching tools
Slide presentations
Exercises
Scientific papers
Office hours
See the website of Rita Casadio
See the website of Osman Ugur Sezerman