Visualising errors in animal pedigree genotype data

  • Authors:
  • Martin Graham;Jessie Kennedy;Trevor Paterson;Andy Law

  • Affiliations:
  • School of Computing, Edinburgh Napier University, UK;School of Computing, Edinburgh Napier University, UK;The Roslin Institute, University of Edinburgh, UK;The Roslin Institute, University of Edinburgh, UK

  • Venue:
  • EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
  • Year:
  • 2011

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Abstract

Genetic analysis of a breeding animal population involves determining the inheritance pattern of genotypes for multiple genetic markers across the individuals in the population pedigree structure. However, experi-mental pedigree genotype data invariably contains errors in both the pedigree structure and in the associated individual genotypes, introducing inconsistencies into the dataset, rendering them useless for further analysis. The resolution of these errors requires consideration of genotype inheritance patterns in the context of the pedigree structure. Existing pedigree visualisations are typically more suited to human pedigrees and are less suitable for large complex animal pedigrees which may exhibit cross generational inbreeding. Similarly, table-based viewers of genotype marker data can highlight where errors become apparent but lack the func-tionality and interactive visual feedback to allow users to locate the origin of errors within the pedigree. In this paper, we detail a design study steered by biologists who work with pedigree data, and describe successive iterations through approaches and prototypes for viewing genotyping errors in the context of a displayed pedigree. We describe how each approach performs with real pedigree genotype data and why eventually we deemed them unsuitable. Finally, a novel prototype visualisation for pedigrees, which we term the 'sandwich view', is detailed and we demonstrate how the approach effectively communicates errors in the pedigree context, supporting the biologist in the error identification task.