Online Program

Statistical methods for analyzing rare variants in next generation sequencing association studies

Tuesday, November 5, 2013 : 4:30 p.m. - 4:50 p.m.

Xihong Lin, PhD, Department of Biostatistics, Harvard School of Public Health, Harvard University, Boston, MA
An increasing number of large scale sequencing association studies, such as the whole exome sequencing studies, have been conducted to identify rare genetic variants associated with disease phenotypes. Testing for rare variant effects in sequencing association studies presents substantial challenges. We first provide an overview of statistical methods for testing for rare variant effects in case-control and cohort studies, and then discuss statistical methods for meta analysis of rare variant effects in sequencing association studies and family sequencing association studies. The proposed methods are evaluated using simulation studies and illustrated using data examples.

Learning Areas:

Biostatistics, economics
Environmental health sciences
Public health biology

Learning Objectives:
Describe statistical methods for analyzing rare variant effects in next generation sequencing case-control, cohort family association studies. Discuss meta-analysis of multiple sequencing association studies. Compare different methods using simulation studies and illustrate them using data examples.

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a biostatistician working on statistical genetics and genetic epidemiology. I have been principal investigator of two NCI grants.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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