Allele Dispersion Score: Quantifying the range of allele frequencies across populations, based on UMAP

Abstract

Genomic variation plays a crucial role in biology, serving as a base for evolution - allowing for adaptation on a species or population level. At the individual level, however, specific alleles can be implicated in diseases. To interpret genetic variants identified in an individual potentially affected with a rare genetic disease, it is fundamental to know the population frequency of each allele, ideally in an ancestry matched cohort. Equity in human genomics remains a challenge for the field, and there are not yet cohorts representing most populations. Currently, when ancestry matched cohorts are not available, pooled variant libraries are used, such as gnomAD, the Human Genome Diversity Project (HGDP) or the 1,000 Genomes Project (now known as IGSR: International Genome Sample Resource). When working with a pooled collection of variant frequencies, one of the challenges is to determine efficiently if a variant is broadly spread across populations or appears selectively in one or more populations. While this can be accomplished by reviewing tables of population frequencies, it can be advantageous to have a single score that summarizes the observed dispersion. This score would not require classifying individuals into populations, which can be complicated if it is a homogenous population, or can leave individuals excluded from all the predefined population groups. Moreover, a score would not display fine-scaled population information, which could have privacy implications and consequently be inappropriate to release. Therefore, we sought to develop a scoring method based on a Uniform Manifold Approximation and Projection (UMAP) where, for each allele, the score can range from 0 (the variant is limited to a subset of close individuals within the whole cohort) to 1 (the variant is spread among the individuals represented in the cohort). We call this score the Allele Dispersion Score (ADS). The scoring system was implemented on the IGSR dataset, and compared to the current method consisting in displaying variant frequencies for several populations in a table. The ADS correlates with the population frequencies, without requiring grouping of individuals.

The variant catalogue pipeline: A workflow to generate a background variant library from Whole Genome Sequences

“…Such analysis sub-workflows could be developed by projects seeking to include such information in their variation catalogue. Alternatively, it is also possible to do similar analysis in a manner that is respectful of project governance choices, such as the development of the allele dispersion score, which allows distinguishing between variants spread across a cohort and variants restricted to subsets of genetically more similar individuals (Correard et al, 2022). This does not require classifying individuals into groups, nor does it require sharing population specific information.…”