Difference between revisions of "ComplexNGS2025"

=Complex Trait Analysis of Next Generation Sequence Data Course=
September 8-12, 2025

Max Delbrück Center (MDC) for Molecular Medicine

Berlin, Germany

----

The seventh annual Berlin Complex Trait Analysis of Next Generation Sequence Data Course will be held at the MDC in Berlin from September 8-12, 2025. 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 and family-based sequence data, and evaluation of variant functionality. Analyses will include performing complex trait rare variant association analysis for population and family data via linear mixed models. Exercises will be carried out using a variety of computer programs that include ANNOVAR, BOLT-LMM, FAST-GWA, IGV, R, REGENIE, PSEQ, & Variant Association Tools (VAT).

TOPICS will 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 for researchers from an academic institution, and €1,950 for individuals from private (for-profit) companies. This fee covers tuition, A Monday evening welcome dinner, and course-related expenses (handouts, etc.) but not room, board, or additional meals. Housing is available for course participants at nearby hotels.

The instructors for the course are Suzanne Leal (Columbia University) and Michael Nothnagel (University of Cologne).

For additional information on the Complex Trait Analysis of NGS Data Course please contact Suzanne Leal:
Email: suzannemleal@gmail.com