Identifying Genes for Mendelian Traits using Next Generation Sequence Data

 

The Identifying Genes for Mendelian Traits using Next Generation Sequence Data Course will be held at the MDC in Berlin from November 5-9, 2018. The goal of the course is to teach the course participants both theory and application of methods to identify genes for Mendelian diseases/traits using filtering methods, homozygosity mapping, and linkage analysis.

The emphasis in this course is on strategies for gene mapping and variant/gene identification for Mendelian Traits. It will include theory as well as practical exercises. The exercises will be carried out using a variety of computer programs (e.g. Gemini, GeneHunter, GERP, Homozygosity Mapper, Integrative Genome Viewer, MERLIN, PhlyoP, Polyphen, SEQLinkage, Variant Mendelian Tools,) and with pencil and paper. TOPICS include: study design; linkage analysis and homozygosity mapping using genotype array and next-generation sequence data (exome and whole genome), haplotype reconstruction, evaluating pedigree informativeness and power to detect linkage, vcf file annotation; generation of NGS data; identification of causal variants using filter approaches, variant annotation, evaluation of deleterious effects of variants and their functionality. The organizers and instructors for the course are 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. 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.

For additional course information including schedule and application please visit the course website:

https://statgen.research.bcm.edu/index.php/NGSMendelian2018

Application deadline July 15th

We are also accepting applications for 

Genetic Association Course: with Application to the Analysis of Sequence and Genotype Data: https://statgen.research.bcm.edu/index.php/Genassoc2018