Difference between revisions of "Advgenemap2022"

Latest revision as of 19:52, 17 January 2022

Advanced Gene Mapping Course

The Rockefeller University, New York 
Welch - The Great Hall
Monday through Friday, January 10-14, 2022

General Information

An Advanced Gene Mapping course will be held in New York from Monday through Friday, January 10-14, 2022. The cost of the 5-day course is $100 for student, academic, and government researchers and $2,500 for researchers working in industry. This fee covers tuition and course-related expenses (cloud computing, etc.).

The course emphasis is on analyzing sequence and other omics data to elucidate the genetic etiology of complex human disease traits. Topics will include: data quality control of sequence and other types of data; single variant and aggregate rare variant association analysis of whole-genome data (genotype, sequence, and imputed) for qualitative and quantitative traits (population and family-based data); controlling for population admixture and substructure; linear mixed models (LMM) and generalized LMM (GLMM); meta-analysis; sample size estimation and power calculations; detecting gene x gene and gene x environmental interactions; heritability estimation; analysis of RNA-Seq data; eQTL mapping; elucidating pleiotropy; functional prediction and variant annotation; estimation of polygenic risk scores; Mendelian randomization; mediation analysis; and fine mapping. As mandated by the NIH there will also be a special session on responsible conduct of research that will include sessions on conflict of interest, research ethics, data management (security), and ethical use of human research subjects. 

A variety of freely available software will be used to perform the practical exercises, due to differences in their functionality.FaST-LMM, REGENIE will be implemented to analyze population- and family-based data by applying GLMM and LMM. Mediation analysis will be performed using R to aid in distinguishing between biological, mediated, and spurious pleiotropy. To make inferences on causality, Mendelian randomization will be performed using MR-base. Estimation of polygenic risk scores will be performed using LDpred. mvSuSiE and SuSiE will be used for fine mapping to aid in the detection of causal susceptibility variants. Heritability estimates will be performed using LDSC. Imputation and Analysis of imputed RNAseq expression data will be performed by applying FUSION; To perform analytical and empirical power analysis for single and rare variant aggregate tests, a variety of tools will be used that includes the Armitage Power Tool and the SKAT R library will be used. Additionally, variant annotation will be performed with ANNOVAR as well as directly using a variety of functional prediction and conservation tools, e.g. CADD, GERP, MutationTaster, MutPred, Polyphen-2, and SIFT.

Course Instructors

The instructors for the course are Heather Cordell (University of Newcastle), Andrew DeWan (Yale University), Suzanne Leal (The Rockefeller University & Columbia University), Shamil Sunyaev (Harvard University) & Gao Wang (Columbia University). Judy Matuk (HRP Consulting Group) will lecture on ethics and the regulation of human subject research. A special guest lecture will be given by Jurg Ott (Rockefeller University).

Additional Information

The maximum number of participants for this course is 32.  

Only individuals who are fully vaccinated for COVID can attend the course. With your application form include a scan of your COVID vaccination documentation. We will be following COVID protocols and the wearing of masks will be required.

The course is wheelchair accessible. All disabilities will be accommodated. Handicapped individuals are encouraged to apply.

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 the selection of participants.  Please describe your experience in detail in your application. It is helpful if you also enclose a copy of your CV. We may contact you personally to discuss your application. Although 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 contact the course organizer Suzanne Leal: 
email: suzannemleal@gmail.com or sml3@cumc.columbia.edu

The deadline for the course application is November 12, 2021

Click here for the course schedule

Click here for the application form

Click here for the course flyer (please post and distribute)

Handouts

Heather Cordell

Lectures

• Genome-Wide Association Studies
• Linear Mixed Models and G×G or G×E interactions

Andy DeWan

Lectures

• Mandelian Randomization: An Introduction
• From Cross-Phenotype Associations to Pleiotropy in Human Genetic Studies

Suzanne Leal

Lectures

• Data Quality Control
• Analysis of Rare Variants
• Power Analysis

Judy Matuk

Lectures

• The Ethics and Regulation of Human Subjects Research

Jurg Ott

Lectures

• Assocaition Analysis of Genotype Patterns with Digenic Traits

Shamil Sunyaev

Lectures

• Analysis of Complex Traits
• Functional Annotation of Coding and Non-coding Variants
• Population Genetics
• Polygenic Risk Scores

Gao Wang

Lectures

• PhenotypePrediction and Transcriptome-Wide Association Studies
• Multivariate Analysis in Genetic Association Studies
• Linkage Disequilibrium in Genetic Association Studies
• Integrating GWAS with Functional Annotations
• Statistical Fine-Mapping in Genetic Association Studies
• Fine-Mapping with Summary Statistics: Current Methods and Practical Considerations

                          This course is supported by funding from the National Human Genome Research Institute.