Interactive Exploration, Analysis, and Visualization of Complex Phenome-Genome Datasets with ASPIREdb

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Identifying causal variants for complex genetic disorders is a significant challenge.
• Whole-exome and whole-genome sequencing generate large variant datasets requiring sophisticated analysis tools.
• Effective correlation of genetic variants with subject phenotypes is crucial for interpreting disease-causing mutations.

Purpose of the Study:

• To develop a user-friendly web application, ASPIREdb, for searching, organizing, analyzing, and visualizing genetic variants and associated phenotypes.
• To enable researchers to annotate variants using public databases and build queries for identifying subjects or variants of interest.
• To facilitate collaborative research by allowing projects to be shared among investigators.

Main Methods:

• Development of a web application (ASPIREdb) integrating variant and phenotype data.
• Implementation of variant annotation using publicly available reference databases.
• Inclusion of query building, burden analysis, and reporting tools for data investigation.
• Facilitation of project sharing for collaborative data annotation and analysis.

Main Results:

• ASPIREdb provides a platform for researchers to search, organize, analyze, and visualize genetic variants and phenotypes.
• The application allows for variant annotation, powerful query construction, and collaborative project management.
• Demonstrated functionality using publicly available datasets, showcasing its utility for researchers without specialized bioinformatics expertise.

Conclusions:

• ASPIREdb simplifies the complex process of identifying disease-causing genetic variants by integrating variant and phenotype data analysis.
• The application enhances collaborative research efforts in genomics and disease genetics.
• ASPIREdb empowers researchers to interpret genetic findings and advance the study of complex genetic disorders.