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

  1. Define classes of non-coding mutations which contribute to ASD risk, reconciling Werling & Turner
  2. Generate more comprehensive gene-level predictions using non-coding sources of variation

Goals:

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