Genetics of Autism
- Genetic contribution to ASD risk ~40-80%
- 850 candidate autism genes, with evidence largely derived from WES
We use machine learning approaches to provide gene-level estimates of autism involvement
Gap: contribution of non-coding mutations to ASD risk largely unknown
Genetics of Autism
Opportunity:
MSSNG(2017)
Werling(2017)
Turner(2017)
5K
2K
2K
| Non-coding contribution to ASD | |||
| Update genome-wide scores |
Not analyzed
Approach: meta-analysis
- Define classes of non-coding mutations which contribute to ASD risk, reconciling Werling & Turner
- Generate more comprehensive gene-level predictions using non-coding sources of variation
Goals: