Difference between revisions of "Advgenemap2023"

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Advanced Gene Mapping Course

The Rockefeller University, New York
Welch - The Great Hall
Monday through Friday, May 22-26, 2003

General Information

An Advanced Gene Mapping course will be held in New York from Monday through Friday, May 22-26, 2003. 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 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; transcriptome-wide association studies (TWAS); analysis of RNA-Seq data; eQTL mapping; elucidating pleiotropy; functional prediction and variant annotation; estimation of polygenic risk scores; Mendelian randomization; mediation analysis; LDclumping 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, GCTA, REGENIE will be implemented to analyze population- and family data by applying GLMM and LMM. PLINK will be used to perform data quality control and association analysis controlling for population admixture and substructures using principal component analysis (PCA) and multidimensional scaling (MDS). REGENIE, VAT, and PSEQ will be used to perform data quality control of sequence data and to perform rare variant aggregate association analysis. Gene x gene and gene x environmental interactions will be tested using PLINK and CASSI. Mediation analysis will be performed using Multiphen and R to aid in distinguishing between biological, mediated, and spurious pleiotropy. To make inferences on causality, Mendelian randomization will be performed using MRbase. MR-JTI will be used to perform TWAS analysis. Estimation of polygenic risk scores will be performed using LDpred2. SuSiE will be used for fine mapping to aid in the detection of causal susceptibility variants. To perform analytical and empirical power analysis for single and rare variant aggregate tests, a variety of tools 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) and Gao Wang (Columbia University). TBN (HRP Consulting Group) will lecture on ethics and the regulation of human subject research. A special guest lecture will be given by Jurg Ott (The Rockefeller University).

Additional Information

The maximum number of participants for this course is 34.

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.

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 submit a copy of your CV with your application as well as a letter describing your expertise/experience in detail, e.g., research and training in statistical genetics or related fields. We may contact you personally to discuss your application. If you do not have experience using Unix/LINUX it is highly beneficial to obtain this knowledge before the start of the course.

For additional information contact the course organizer Suzanne Leal:

email: suzannemleal@gmail.com or sml3@cumc.columbia.edu

Application Deadline: March 31, 2023