C8702 - STATISTICAL APPROACHES TO ASSESS HUMAN MOLECULAR VARIABILITY

Learning outcomes

The course will focus on the most up-to-date statistical approaches aimed at investigating patterns of human molecular variability and at inferring the biological processes that have shaped them. By the end of the course, students will develop understanding of the key concepts and models useful to study and quantify molecular variation within and among human populations, and will acquire knowledge on the most advanced technologies to generate genome-wide and whole-genome sequence data, as well as on the theoretical and methodological aspects related to statistical methods developed to analyze them.

Course contents

The course contents will be organized according to the following main arguments:

• Key concepts in the study of human molecular variability.

• Main technologies for generating genome-wide and whole-genome sequence data.

• Data types and extraction of genomic information from public databases.

• Procedures for dataset assembly, data quality controls, genotype imputation and haplotype phasing.

• Statistical approaches to investigate population genetic structure and infer ancestry profiles.

• Statistical methods to estimate patterns of allele sharing between individuals and population groups.

• Models and inferential methods to test and dating relationships and gene flow among populations.

• Tools for data visualization and graphical representation of results from statistical analyses.
  

Readings/Bibliography

Lectures slides as well as selected scientific articles and review papers focused on the main arguments discussed during the course, will be shared with the students by means of dedicated tools (e.g. Virtuale website).

For students who want to further deepen some topics, the following textbook is suggested:

Jobling, Hollox, Hurles, Kivisild, Tyler-Smith. 2014. Human Evolutionary Genetics (II edition). Garland Science, Taylor & Francis Group

Teaching methods

The course consists of 6 ECTS that will be supplied by means of frontal lessons with PowerPoint presentations, complemented with in-class discussion of primary research literature for in-depth exploration of specific topics.

Students with special needs and/or certifications are asked to contact the teacher by e-mail, entering DSA service in Cc (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students).

Assessment methods

The exam aims to assess the achievement of the learning objectives and consists of a written test made up of a combination of open-ended and multiple-choice questions on the arguments treated during the lessons. The final mark (expressed in thirtieths) is defined by the sum of the scores obtained in each question.

As regards the assessment of learning, the use of AI is prohibited during the exam. Any use constitutes a violation of academic integrity.

Students with learning disorders and\or temporary or permanent disabilities: please, contact the office responsible (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students) as soon as possible so that they can propose acceptable adjustments. The request for adaptation must be submitted in advance (15 days before the exam date) to the lecturer, who will assess the appropriateness of the adjustments, taking into account the teaching objectives.

Students recognized as “working students”: please consult the dedicated website (https://www.unibo.it/en/study/guide-to-choosing-your-programme/balancing-study-and-work) to apply for this status and to learn about the available measures.

Teaching tools

Lectures will be delivered using PC, projector and Blackboard/whiteboard.

The PDF/PPT slides of the lectures and the scientific literature in support will be shared with the students by means of dedicated tools (e.g. Virtuale)

Office hours

See the website of Stefania Sarno