TORONTO, Ontario (PRWEB) November 14, 2019
Genome-wide association studies (GWAS) present a viable approach for researchers to identify genetic variations associated with a particular trait. GWAS have already identified several single nucleotide polymorphisms associated with diabetes, Parkinson’s disease, amongst others. However, these comprehensive studies frequently identify large numbers of genetic variants associated with the phenotypes, not all of which are causal. Researchers seek to understand which variants narrowly missed the threshold but actually are causal.
Fine mapping, a statistical process in which additional data are introduced to the GWAS dataset, enables researchers to prioritize those variants that warrant additional examination, but assembling the data and building the proper computing environment to perform fine mapping is time-consuming and challenging.
DNAnexus’ Product Manager Eugene Miloslavsky will be the host of a live webinar featuring DNAnexus’ Senior Machine Learning Engineer and Data Science Lead, Peter Nguyen. This webinar will take place on Thursday, December 5, 2019 at 12pm EST and will feature a live Q&A session at the end.
At the end of this webinar, attendees will:
- Understand the applications and benefits of fine mapping for refining GWAS results
- Learn about the computing environment needed for fine mapping
- Gain strategies for building and deploying interactive machine learning models
- See the DNAnexus platform and how it enables machine learning in a secure and scalable environment
For more information or to register for this event, visit Optimizing GWAS Results Using an Interactive Machine Learning Approach.
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