Predicting the effect of variants on splicing.
Based on the maximum entropy model, According to the ClinGen variant curation expert panel consensus guidelines for LDLR variant classification. We use Mutalyzer v2.0.34 and MaxEntScan web services to predict the effect.
Example: You can explore the reports by entering c.244T>A as an example for a valid HGVSc variant name in the website's input box.
The final version is ready at https://maxsplizer.com. The front-end is developed by Reza Shahnazar as a Single-Page-Application using Vue3 framework and some Javascript libraries. The predictor back-end is an R-plumber api project developed by Seyedmohammad Saadatagah. It uses Mutalyzer v2.0.34 and MaxEntScan web services as dependencies.
The project is developed in Atherosclerosis and Lipid Genomics Laboratory under the supervision of Dr. Iftikhar Kullo.
The R project could be served in a docker container. Nginx could be configured using the "front-end/nginx.conf" file to serve the production build of the Vue app from "/app" directory on a linux server. Nginx would also redirect all HTTP requests with the endpoint of "/maxent" to the docker port.