Population Approaches to Detecting and Genotyping Copy Number Variation

1. Population Approaches to Detecting and Genotyping Copy Number Variation Lachlan Coin July 2010

2. Outline Population-haplotype approach to CNV detecting and genotyping Application to SNP and CGH data Application to NGS sequence data

3. cnvHap approach to CNV discovery and genotyping

4. Example of trained model

5. cnvHap models haploid CN transitions Specify an per-base global transition rate matrix

6. cnvHap joint model of CNV + SNP haplotypes

7. Cluster positions modelled using a linear model

8. Using Illumina SNP arrays

9. Combined Illumina and Agilent arrays

10. Some CNVs exhibit shared structure

11. Improved CNV genotyping accuracy

12. A deletion at 16p11.2 in a patient with �extreme obesity�

13. 16p11.2 deletions in obesity and population cohorts

14. Coverage affected by GC content

15. Regression model fit to correct for GC bias

16. Loess curves fit to remove residual spatial variation of coverage

17. Detecting CNVS with NGS data

18. NGS versus CGH data

19. NGS vs CGH data

20. Haplotype structure of deletion

21. NGS amplification

22. With consistent break-points in population

23. Polyploid phasing and imputation

24. Conclusions Population-haplotype model enables joint CNV discovery and genotyping using array data Preliminary results indicate this will also help using NGS data Combining information from multiple platforms improves sensitivity Imputation still works for ploidy > 2, phasing becomes more difficult

25. Acknowledgements