JSM 2009: Overcoming data quality and copy number detection issues in genome-wide CNV association studies.

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

Date: August 5, 2009 - 11:00AM EST

Duration: 90 Minutes

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Abstract

Though CNV association studies show great promise, data quality issues make this potential gold mine a quagmire. CNV quality issues have been a persistent problem on the 20+ CNV GWAS we have performed on multiple microarray and aCGH platforms. The impact of batch effects and other quality issues leads to complications ranging from poorly defined segments to false and non-replicable findings. Our PCA approach simultaneously corrects for batch and wave effects and population stratification, while significantly improving signal-to-noise ratios. Combining this with novel segmentation-based calling methods gives improved sensitivity and FDR. Several approaches to genome-wide scans for CNV association are shown, leading to significant findings across many studies. Our results suggest there is a wealth of CNV associations that explain much of the heritability not accounted for by SNPs.

About the Presenter

Dr. Christophe Lambert is the President 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.