Survey
* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
Download Day2PM_Variant_Prioritization
Document related concepts
no text concepts found
Transcript
Variant Prioritization in Disease Studies 1. Remove common SNPs Credit: goldenhelix.com 2. Remove common exonic SNPs (from large WES studies) Credit: goldenhelix.com 3. Select amino acid changing variants Credit: goldenhelix.com 4. Find variants that have potential functional effect Credit: goldenhelix.com Predicting functional effects • Conservation across species • Amino acid properties • Protein structure • Transmembrane regions, signal peptides etc. Annovar: Annotate variants with all these annotations • http://www.openbioinformatics.org/annovar/ • Web version: http://wannovar.usc.edu/ Web ANNOVAR - basic Web ANNOVAR - Advanced Most times that’s still not enough to find a causative variant If the list is still too large and/or no obvious candidate variant stands out… Then we go ‘digging’ in the context of existing knowledge about genes, their product functions and known involvement in phenotypes and diseases… Typical questions bioinformaticists ask (or should): • Is the variant in a known disease gene? • Is it in a gene involved in a related disease? • Does the gene have a function that coincides with the pathology, biochemistry, etc? • Is the gene product in a pathway associated with the disease? THANK YOU (Please fill out the feedback form) [email protected]
Related documents