Registration for a live webinar on 'Precision medicine treatment for anticancer drug resistance' is now open.
See webinar detailsWe noted you are experiencing viewing problems
-
Check with your IT department that JWPlatform, JWPlayer and Amazon AWS & CloudFront are not being blocked by your network. The relevant domains are *.jwplatform.com, *.jwpsrv.com, *.jwpcdn.com, jwpltx.com, jwpsrv.a.ssl.fastly.net, *.amazonaws.com and *.cloudfront.net. The relevant ports are 80 and 443.
-
Check the following talk links to see which ones work correctly:
Auto Mode
HTTP Progressive Download Send us your results from the above test links at access@hstalks.com and we will contact you with further advice on troubleshooting your viewing problems. -
No luck yet? More tips for troubleshooting viewing issues
-
Contact HST Support access@hstalks.com
-
Please review our troubleshooting guide for tips and advice on resolving your viewing problems.
-
For additional help, please don't hesitate to contact HST support access@hstalks.com
We hope you have enjoyed this limited-length demo
This is a limited length demo talk; you may
login or
review methods of
obtaining more access.
Printable Handouts
Navigable Slide Index
- Introduction
- Structure of presentation
- What are whole-genome association studies?
- Why do whole-genome association studies?
- Steps in WGA study
- Example: HIV setpoint
- Phenotype definition
- Natural history of HIV disease
- Setpoint: the real world
- How to define the setpoint?
- Whole genome genotyping panels (1)
- Whole genome genotyping panels (2)
- PLINK
- QC of genotype data
- QC of genotype/phenotype match
- Stratification can lead to false positives
- Implications of differences in disease rates
- PCA method can reveal hidden groups
- PCA for SNP data ("EIGENSTRAT")
- PCA properties
- Modified EIGENSTRAT procedure
- SNP-by-SNP analysis
- X chromosome SNP-by-SNP analysis
- Options for modeling the X
- Multiple testing approaches
- Bonferroni method
- Q-Q (quantile-quantile) plot
- HIV setpoint illustrating usefulness of Q-Q plot
- False discovery rate
- Permutation
- Why is the dependence of tests not too crucial?
- "Outright hits" is not huge gain in power (1)
- "Outright hits" is not huge gain in power (2)
- FDR is unaffected for large pools (1)
- FDR is unaffected for large pools (2)
- Variance of FDR is affected
- Bayesian alternatives
- Bayes factor
- Bayesian false discovery probability (BFDP)
- Genomewide-significant SNPs in HLA region
- HLA-C effect is mediated via expression
- Additional topics
- Acknowledgements
- References (1)
- References (2)
- References (3)
- References (4)
Topics Covered
- What are whole-genome (genome-wide) association studies and why do them?
- Steps in WGA study
- HIV setpoint
- Phenotype definition
- Setpoint
- Whole genome genotyping panels
- PLINK
- Cryptic population stratification
- PCA and EIGENSTRAT
- SNP-by-SNP analysis
- Multiple testing approaches
- Bonferroni method
- Q-Q (quantile-quantile) plot
- False discovery rate
- Permutation
- Outright hits
- Pool of hits
- Bayesian alternatives
- Bayes factor
- Bayesian false discovery probability (BFDP)
Talk Citation
Weale, M. (2007, October 1). Whole-genome association studies: practical advice and considerations [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 26, 2024, from https://doi.org/10.69645/KTNP2835.Export Citation (RIS)
Publication History
Financial Disclosures
- Dr. Mike Weale has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
Hide