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New genome panel helps infer the part from the whole

Published online 24 August 2016

A large “reference panel” of full genetic data allows researchers to more accurately infer information from cheaper-to-obtain partial genomes.

Nadia El-Awady

An international consortium of researchers has gathered whole-genome sequence data from 20 studies to develop a “reference panel” that allows researchers to accurately infer genetic information from partial genome data1.

“Genotype imputation is a method that allows us to combine partial information about a person’s genome, which can be much cheaper to obtain, with full genome sequences from other people to make a very good guess about the missing sequence in that person’s genome,” explains geneticist Richard Durbin from the UK’s Wellcome Trust Sanger Institute. 

The larger the reference panel, the more accurately researchers can infer information from partial genomes about genetic mutations of research interest, says Durbin.

The consortium collected full genome data from 32,488 individuals and then applied statistical methods to infer their haplotypes — the set of genes inherited from each parent. They then compiled a reference panel composed of these haplotypes.

The current reference panel includes genomic data from people of predominantly European ancestry, but the team is building a second release that will include genetic data from all over the world to provide a more global resource, says Durbin, making it more accurate.

Researchers have already been using the new haplotype panel over the past year to impute the genome sequences of over two million individuals to investigate genetic factors involved in a wide range of diseases, including heart disease, diabetes and psychiatric disease.

The reference panel is available on Internet servers based at the Wellcome Trust Sanger Institute in the UK and the University of Michigan in the US.

doi:10.1038/nmiddleeast.2016.127


  1. McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. http://dx.doi.org/10.1038/ng.3643 (2016).