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Yiliang Ma

Graduated: August 21, 2020

Thesis/Dissertation Title:

Everyone’s Variant Annotation Tools: EVAT

Currently, there is a lot of genetic variant information distributed in many different databases, and it will cost individuals plenty of time to retrieve data from those resources.
In this thesis, I develop EVAT(Everyone’s variant annotation tool), a tool aiming at helping individuals retrieve annotation information about their genetic variants. People with or without programming skills may choose different methods to get their genetic variant annotation information. For individuals who have program skills, EVAT offers Python APIs which connect to the backend directly to help them retrieve annotation information. The backend of the tool is built by four file interpreters that translate file format, a module that sends and receives information from, a module that converts the JSON result from to Panda dataframe and three functions that support different queries. For individuals who don’t have program skills, EVAT offers a graphical user interface, which is the front end of the tool. This user interface allows users to upload files, read the annotation, and do the query by mouse so that they don’t need coding skills when doing genetic annotation.
EVAT can be used either as a backend only (for users with programming skills) or with a graphical user interface to easily query and retrieve annotation information. This annotation information could help people understand the effect of genetic variants or do further research about them.