ComplexNGS2020
From Statistical Genetics Courses
Complex Trait Analysis of Next Generation Sequence Data Course
November 23-27, 2020
Max Delbrück Center (MDC) for Molecular Medicine
Berlin, Germany
The sixth annual Berlin Complex Trait Analysis of Next Generation Sequence Data Course will be held at the MDC in Berlin from November 23-27, 2020. The goal of the course is to teach both the theory and application of methods to analyze next-generation sequence (NGS) data for human complex traits. Attendees will learn how to design studies, call variants from NGS data, analysis of population-, trio- and family-based sequence data and evaluation of variant functionality. Analyses will include performing complex trait rare variant association analysis for population and trio data. Exercises will be carried out using a variety of computer programs that include ANNOVAR, BOLT-LMM, IGV, R, PSEQ, & Variant Association Tools (VAT).
TOPICS will be include: sequence alignment, calling variants from NGS data, quality control of NGS data, association testing framework for quantitative and qualitative traits (fixed effects, random effects and generalized linear mixed models and linear mixed models), rare variant association methods, polygenic risk scores, estimating power and sample size for rare variant association studies, imputation of rare variants and their analysis, and evaluating variant conservation and functionality.
The cost of the 5-day course is 975 EUR for researchers from an academic institution, and 1,950 EUR for individuals from private (for profit) companies. This fee covers tuition, Monday evening wine and cheese party and course related expenses (handouts, etc.) but not room, board or meals. Inexpensive housing is available for course participants at the MDC and nearby hotels.
The organizers and instructors for the course are Suzanne Leal (Columbia University) and Michael Nothnagel (University of Cologne).
Application Deadline September 1, 2020
For additional information on the Complex Trait Analysis of NGS Data Course please contact Suzanne Leal: Email: suzannemleal@gmail.com
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