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Navigable Slide Index

1. Introduction
2. Outline of the talk
3. Classes of structural variation
4. Why study CNVs?
5. SNPs and CNVs
6. CNV detection assays
7. Data pre-processing
8. Sample QC (1)
9. Sample QC (2)
10. Discovery vs. genotyping
11. CNV discovery algorithms
12. CNV discovery in WTCCC1 (1)
13. CNV discovery in WTCCC1 (2)
14. CNV maps
15. CNV regions (CNVR) (1)
16. Extraction of CNV signal
17. Summarize using mean
18. Summarize using first PC
19. Other sources of information on CNV genotype
20. CNV regions (CNVR) (2)
21. CNV association strategies
22. Differential bias
23. Overdispersion, differential means and variances
24. Integrated approach to genotyping and association
25. Controls vs. controls
26. Power vs. clusterability (Q)
27. Hollox et al. data
28. Rare variant associations
29. Gene ontology enrichment
30. Gene/genomic window enrichment
31. Conclusions
32. References
33. Reported CNV associations

Topics Covered

• Background on copy number variation biology
• Preprocessing and normalization of array data
• QC techniques for CNV data
• CNV discovery
• Impact of differential bias on CNV associations
• Methods for testing common CNVs in association studies
• Methods for testing rare CNVs in association studies

Links

Series:

• Statistical Methods for the Analysis of Genome-Wide Association Studies

Categories:

• Genetics & Epigenetics
• Methods

Talk Citation

Publication History

• Published on June 4, 2008
• Archived on February 25, 2021

Financial Disclosures

• Dr. Don Conrad has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.