Course C295/01 Bayesian statistics with applications in genomics

ECTS: 3.9

Course leader: Jakob Skou Pedersen

Language: English

Graduate school: Faculty of Health

Max seats: 25

Applicants: 19

Status: Course is closed for applications

Application deadline: 02/11/2020

Start date: 30/11/2020

Administrator: Annette Poulsen

Title: Bayesian statistics with applications in genomics

Reg.no: C295/01

is being offered by the Graduate School of Health, Aarhus University, fall 2020

Criteria for participation: The course targets computer scientists, bioinformaticians, and biologists or clinicians with strong drive towards informatics and data analysis. The participants should have a university degree in the above disciplines and / or be postgraduate research fellows (PhD students and research-year medical students).

Aim: To apply Bayesian statistics in the analysis of biological or clinical data.

Learning outcomes:

  • To understand the principles and central concepts of Bayesian statistics
  • Be able to translate and formalize simple scientific questions to ayesian models
  • Be able to perform Bayesian statistical analysis in R and Stan
  • To understand and apply a range of inference methods

Content:

  • Bayesian statistics concepts (ideas, priors and posteriors, updating…, MAP and other measures on the posterior)
  • Statistical model formalism and specification in R / Stan
  • Inference: MAP using grid evaluation; perhaps normal approximations
  • More advanced Bayesian stats concepts (posterior predictive value, model selection)
  • Inference: MCMC -- basic concepts, implementation of MH sampler on some simple problem, and use in modern inference engines
  • Information criteria
  • Variational inference techniques
  • Comprehensive practical exercises and workshops using R and Stan on data analysis
  • Full day hackathon with focus on your own problem and data or locally available data and open problems
  • Guest lectures on statistical data analysis, problems in genomics, clinical data analysis

Language: English

ECTS: 3.9

Head of course: Prof. Jakob Skou Pedersen (and Asst. Prof. Lasse Maretty), MOMA

Instructors: Data analyst Simon Drue, PhD stud. Simon Grund Sørensen, post doc Mikkel Hovden

Number of participants: 25

Time and date: 30 Nov. - 4 Dec. 2020 from 8:30 - 16:30 every day - with an optional hackathon on day 4 after end of course day.

Place: Kollokvierum Øst, The Victor Albeck building, Vennelyst Blvd. 4, 8000 Aarhus.

Course fee: DKK 4.680

Participation in the course is without cost for:

  • PhD students, Research Year students and Research Honours Programme students from Aarhus University
  • PhD students enrolled at partner universities of the Nordoc collaboration
  • PhD students from other institutions in the open market agreement for PhD courses

Application deadline: 2 November 2020

Application: https://service.health.au.dk/modules/Course/mypage/coursecalendar.