Webcast: Achieving Genome-Wide Success in SNP and CNV Studies

Presenter: Dr. Christophe Lambert, Golden Helix CEO and Co-Chair of the FDA MAQC CNV Team

Date: February 18, 2009 - 11:00AM EST

Duration: 90 Minutes

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Abstract

Continued advances in genotyping technologies, combined with industry-wide efforts to make data publicly available, have given scientist around the world access to a great wealth of genetic data. But due to the increasing scope and complexity of this data, analysis is becoming increasingly difficult.

In this webcast Dr. Christophe Lambert examines some of the more persistent challenges he has experienced in over twenty genome-wide association studies carried out by Golden Helix and its collaborators. Novel methods and technologies are then presented to help you overcome these challenges in your own studies.

Topics Discussed

• Generating accurate genotype calls in the presence of batch effects
• Quality assurance filtering on both samples and genetic markers
• Correcting for batch effects, genomic waves, and population stratification
• Employing genetic models and statistical tests for SNP association
• Calculating copy number covariates and performing CNV association testing
• Utilizing advanced regression techniques
• Interpreting and communicating SNP and CNV findings in genomic context

About the Presenter

Dr. Christophe Lambert is the Chairman and CEO of Golden Helix, Inc., a bioinformatics company he founded in Bozeman, MT in 1998. Dr. Lambert graduated with his Bachelors in Computer Science from Montana State University in 1992 and received his Ph.D. in Computer Science from Duke University in 1997. Dr. Lambert is also currently the co-chair of the Food and Drug Administration’s Genome Wide Copy Number Variation Data Analysis Team of the Microarray Quality Control Consortium.