Developing and Using an R Package To Identify Causative Variations Driving Gene eQTL

Document Type


Publication Date

Summer 2022



JAX Location

In: Student Reports, Summer 2022, The Jackson Laboratory


The use of diversity outbred (DO) mice in biomedical research in academia have been an established tool for researchers since the late 19th century. Mouse embryonic stem cells (mESCs) are the type of strain mice that are used in the research in the Jackson Laboratory because they provide researchers the ability to study diseases and illnesses that would otherwise be too difficult to control in a mammalian population(. In virtually all living organisms, the physical development resulting from the organism maturing into adulthood is defined by the genetics of that animal. We can use various algorithms and fine mapping tools to help us find the causal variants that impact the development of expressive quantitative trait loci in the animals that have the potential to develop these genetic variants that would cause these differences in genomes. For my project, I was provided the Lab's pipeline algorithm, which was constructed as a project by a previous summer student. In my project, I will alter and optimize the pipeline before applying the method in the R package that I will construct in order to reach the goal of finding alternative methods to score eQTLs. This R package will be utilized as an aid for users in detecting causal variants that have a significant effect in the presence of eQTLs. We've devised a strategy for predicting causal variation based on a single gene's expression at a specific place. There is a call to create new code to apply to the R package, such as a column checking algorithm and a TAD identification script.

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