Complex Trait Analysis of Next Generation Sequence Data

March 23-27, 2015
Max Delbrück Center (MDC) for Molecular Medicine
Berlin, Germany

The second annual course on Complex Trait Analysis of Next Generation Sequence Data will be held at the MDC in Berlin from March 23-27, 2015. The goal of the course is to teach the course participants 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 trio- 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 (GATK, IGV, IMPUTE2, Polyphen2, PSEQ, SEQPower, and 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 mixed models), rare variant association methods, estimating power and sample size for rare variant association studies, imputation of rare variants and their analysis, detecting putative causal variants for Mendelian traits and evaluating variant functionality.

The instructors for the course are Laurent Francioli (University Medical Center Utrecht), Suzanne Leal (Baylor College of Medicine) and Michael Nothnagel (University of Cologne).

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 maximum number of participants is 40.

For additional information on the course please contact Suzanne Leal:

Email: sleal@bcm.edu
Phone: +1 (713) 798-4011
Fax: +1 (713) 798-4012