IGES 2008: Methods and Discoveries Drawn from 20 Whole Genome Copy Number Variation Studies

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

Date: September 16, 2008

Duration: 20 Minutes

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Abstract

With over a dozen ongoing collaborations with leading research organizations and access to a wealth of whole genome studies across multiple platforms, we have seen specific, common themes emerging. One of the most persistent and challenging issues has been batch effect correction. With high genotyping call rates mostly unaffected by plate effects, the vast majority of research groups have either insufficiently randomized cases and controls on plates, or borrowed controls from other experiments. Unfortunately, copy number analysis is very sensitive to batch effects.

We have employed PCA-based approaches to mitigate the enormous confounding of CNV association studies by batch effects and population stratification. This presentation will primarily focus on methods of data processing, whole genome association analysis and the challenges of CNV segmentation using the various Wellcome Trust case/control studies (~2000 cases, ~1500 common controls) on Rheumatoid Arthritis, Bipolar Disorder, Coronary Artery Disease, Crohn’s Disease, Hypertension, Type I Diabetes, and Type II Diabetes. Further, in looking at over 20 different studies, we have seen particular regions of chromosome 7 and 14 persistently associated across a vast majority of diseases, regardless of genotyping platform. We have also found perhaps 30-40% of CNV associations are confirmed by past studies, whereas the remaining 60-70% represent novel findings. Corroborated CNV associations of note in the Wellcome Trust studies are regions in or near CHL1, PPP1R12B, SLC8A1, SMAD6 in Coronary Artery Disease, CHL1 in Bipolar Disorder, BTNL2 in Rheumatoid Arthritis, PTPRD in Hypertension, and GGTL4 in Type I Diabetes.

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.