A novel way of visualising eQTLs relative to SNP-SV pairs using Gosling.js
S. Ruff (TU Delft - Electrical Engineering, Mathematics and Computer Science)
N. Tesi – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Andy Zaidman – Graduation committee member (TU Delft - Software Technology)
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Abstract
Genome-wide association studies (GWAS) are commonly used to identify genetic variants associated with human traits by comparing genetic differences between diseased and healthy individuals. One way to gain insights into the biological consequences of these variants is to use quantitative trait locus (QTL) analysis. These connect SNP with variations in gene expression levels among individuals. QTL studies are mostly done on single nucleotide changes, but as SVs are bigger and have greater impact on traits, SV-QTL connections are of great interest. Using Gosling.js, a tool was developed to easily display the links and significance between SNPs, associated eQTLs, and SVs. The main purpose of this tool is to provide clear visualizations, while also offering options for further exploration of the chromosome. The existing search functionalities from snpXplorer have been integrated and enhanced. Users can define a variable window size before querying, allowing for flexible data examination. Additionally, the tool supports requests for data across multiple tissues. For improved performance and usability, the option to select which data tracks are shown were added.