Chromopainter – Identifying shared ancestry

The ability to identify the origin of an individual through quantifying the degree to which its DNA is shared with other populations is a powerful tool. If done accurately, it can provide insight into evolution, migration and ancestral mixing events. This would not only apply to humans, but also to many other species throughout the animal kingdom.

Researchers at the University of Oxford have developed an algorithm which can precisely identify stretches of DNA reflecting shared ancestry and compare these to a reference panel. This algorithm currently represents the most accurate and powerful tool for carrying out these ancestral analyses.

Ancestral analysis

Tracing the genetic origin of a species can provide unprecedented insight into the history of a population. By comparing the DNA of individuals, genetic analyses can unearth information about the geographical and temporal ancestral relatives of an individual or group. This technology has wide ranging applications from disease mapping to understanding human history.

Analysis methods

Accurately identifying segments of DNA that individuals have inherited from different ancestral sources can be highly challenging.
Previous methods have used data that is too coarse, leading to ambiguous predictions, or they have failed to account for linkage disequilibrium, the connection between several alleles at different loci, potentially resulting in misleading or incomplete inferences.

Chromopainter – ancestry evolved

Oxford researchers have developed Chromopainter, an algorithm that analyses data from dense genotyping chips to infer local ancestry with very high precision. It is the most accurate tool of its kind as it makes use of key haplotypes, groups of genes that are inherited concurrently. These haplotype markers are known to be more informative than the simple use of individual loci. Simulations have demonstrated the ability of Chromopainter to uncover previously unknown aspects of population history.

The key benefits of the Chromopainter method are as follows:

  • Analyses dense, large-scale diploid data from individuals with mixed ancestry
  • More powerful than existing approaches at inferring ancestry
  • Increased precision to distinguish between closely related ancestral sources
  • Utilises haplotype information that many previous approaches ignore

The software is copyright protected and Oxford University Innovation would like to speak to companies who may be interested in using the Chromopainter algorithm.

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