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GeneOnEarth: fitting genetic PC plots on the globe
Sergio Torres-Sánchez1, Nuria Medina-Medina1, Chris Gignoux2
1CITIC-Universidad de Granada, Granada.
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|December 17, 2013
Summary
GeneOnEarth visually assesses if genetic distances match geographical origins using Procrustes analysis. This tool helps determine if an isolation-by-distance model applies to genetic data, linking genetic variation to geographic locations.
Area of Science:
- Population genetics
- Bioinformatics
- Geographical genetics
Background:
- Principal component (PC) plots are common for visualizing genetic variation.
- Genetic distances in PC plots often correlate with geographical distances.
- Accurate ancestral origins are frequently unknown or unevenly distributed, hindering geographical linkage.
Purpose of the Study:
- To introduce GeneOnEarth, a web-based tool for evaluating isolation-by-distance models in genetic datasets.
- To enable geneticists to visually assess the relationship between genetic and geographical distances.
- To provide a user-friendly platform for exploring genetic variation in a geographical context.
Main Methods:
- Utilizes a by-view Procrustes method for visual comparison of genetic and geographical distances.
- Integrates Google Maps and Google Earth for interactive geographical area selection and manipulation.
- Includes functionality to compute optimal rotation angles and assess statistical similarity.
Main Results:
- GeneOnEarth facilitates the visual assessment of the "isolation-by-distance" model.
- The tool allows users to interactively explore geographical origins on 2D or 3D maps.
- It provides methods to statistically evaluate the congruence between genetic and geographic distances.
Conclusions:
- GeneOnEarth is a valuable tool for geneticists studying the relationship between genetic variation and geography.
- The web-based platform simplifies the analysis of isolation-by-distance patterns.
- It enhances the understanding of how geographical factors influence genetic structure.
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