Advgenemap2019

Advanced Gene Mapping Course

The Rockefeller University, New York
Welch – The Great Hall
Monday through Friday, January 28-February 1, 2019

General Information

An advanced gene mapping course will be held in New York from Monday through Friday, January 28-February 1 2019. The cost of the 5-day course is $100 for student, academic and government researchers and $2,800 for researchers working in industry. This fee covers tuition and course-related expenses (handouts, etc.) but not room and board.

The course emphasis is on the analysis of complex human disease traits; concentrating on methods to detect rare and common variant associations. The course includes theory as well as practical exercises. The exercises will be carried out using a variety of computer programs including BEAM3, GERP, GotCloud, GenAbel, Matrix-eQTL, PLINK, PrediXCan, Polyphen-2, R, SEQPower, Variant Association Tools (VAT), etc. Topics include: Analysis of whole genome association studies; analysis of rare variants using next-generation sequence data; analysis of qualitative and quantitative traits (population and family-based data); Linear mixed models; eQTL mapping; prediction models using RNAseq and array data; inferences for heritability estimation and prediction; functional prediction of variant sites, variant annotation; variant calling, controlling for population substructure\admixture (principal components analysis\multidimensionality scaling); data quality control of genotype and sequence data; meta-analysis; gene x gene interaction; sample size estimation and evaluating power for common and rare variants.

Course Instructors

The instructors for the course are Goncalo Abecasis (University of Michigan), Heather Cordell (University of Newcastle), Nancy Cox (Vanderbilt University), Suzanne Leal (The Rockefeller University & Baylor College of Medicine), and Shamil Sunyaev (Harvard University).

More Information

The maximum number of participants is 30. The course will take place in the Great Hall in Welch at The Rockefeller University, Students will perform exercises by connecting to the cloud using their own laptops. Laptops are also available for students to use for the duration of the course. The course is wheelchair accessible. All disabilities will be accommodated. Handicapped individuals are encouraged to apply.

Four travel stipends of up to $1,000 each are available. Eligibility requirements are: (1) sufficient background and practical experience in statistical analysis of genetic data, and (2) demonstrated financial need. Preference for stipends will be given to pre-doctoral students and postdoctoral researchers. To apply for such a stipend, please attach a letter of request and enclose a letter of reference and proof of student or postdoctoral status.

Knowledge genetic association analysis, genetic epidemiology and/or statistical genetics are screening criteria for selection of participants. Please describe your experience in detail in your application. We may contact you personally to discuss your application. Although the experience of using LINUX is not necessary it is highly beneficial to have basic knowledge of this operating system before the start of the course.

For additional information, please contact Katherine Montague:
email: montagk@rockefeller.edu
Tel: +1 (212) 327-7979

For additional information on scientific program contact the course organizer Suzanne Leal:
email: sleal@bcm.edu or suzannemleal@gmail.com
Tel: +1 (713) 798-4011

Click here for course flyer – Please Post and Distribute

Click here for course schedule

Lecture Handouts

Gonçalo Abecasis

• Presentations
  • Genome-wide Analysis
  • Genotype Imputation
  • Meta Analysis
  • Sequencing

Heather Cordell

• Presentations
  • Genome-wide Association Studies - case/control and family-based
  • Mixed Models and Family-Based Methods
• Exercises
  • Family-based Association Analysis - FaST-LMM, PLINK and R
  • Mixed models Association Analysis Computer - GCTA, PLINK, and R

Nancy Cox

• Presentations
  • Data Integration

Suzanne Leal

• Presentations
  • Data Quality Control
  • NGS Data Quality Control
  • Complex Trait Association Analysis of Rare Variants
  • Family Based Rare Variant Association Analysis: Trios, Sibpairs and Extended Families
  • Power Analysis for Individual Variants and Rare Variant Aggregate Association Analysis

Shamil Sunyaev

• Presentations
  • Genetic Risk Prediction
  • Evolution, maintenance and allelic architecture of complex traits
  • Annotating gene sequence variation
  • Intro to population genetics

Practical Exercises

• Exercise Booklet

• Genome-wide Association Analysis - Quality Control - PLINK
• Genome-wide Association Analysis - MDS and PCA – PLINK
• Sequence data quality control and association analysis (VAT)
• Association Analysis of Sequence Data using PLINK/SEQ (PSEQ)
• Rare-Variant Transmission Disequilibrium Test (RV-TDT)
• Power and Sample Size Calculations – Cochran Armitage Test for Trend
• Functional Annotation

• MaCH
• METAL
• RAREMETAL

Exercise Data Sets

• Genome-wide Association Analysis - Quality Control - PLINK
• Genome-wide Association Analysis - MDS and PCA – PLINK
• Family-based Association Analysis- FaST-LMM, PLINK
• Mixed models Association Analysis Computer – GCTA, PLINK and R
• Sequence data quality control and association analysis (VAT)
• Association Analysis of Sequence Data using PLINK/SEQ (PSEQ)
• Rare-Variant Transmission Disequilibrium Test (RV-TDT)
• Functional Annotation
• MaCH
• METAL
• RAREMETAL

Commands

• Genome-wide Association Analysis-Quality Control-PLINK
• Genome-wide Association Analysis-MDS and PCA-PLINK
• Family-based Association Analysis- FaST-LMM, PLINK and R
• Mixed models Association Analysis Computer – GCTA, PLINK and R
• Sequence data quality control and association analysis (VAT)
• Association Analysis of Sequence Data using PLINK/SEQ (PSEQ)
• Rare-Variant Transmission Disequilibrium Test (RV-TDT)
• Functional Annotation

Software

• ANNOVAR
• FasT-LLM
• GCTA
• MaCH
• METAL
• Minimac
• PLINK
• PLINK/SEQ
• RAREMETAL
• RV-TDT
• SEQPower
• Variant Association Tools

This course is supported by a grant from the National Institute of Health (NIH) - National Human Genome Research Institute (NHGRI).