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The assumptions of prediction tools are described by something called the "heritability model". Most existing tools assume the GCTA Model. This figure shows that for four different tools (from left to right, lasso, ridge regression, Bolt-LMM and BayesR), prediction accuracy always increases when one switches from the GCTA Model to more realistic heritability models (e.g., the LDAK-Thin and BLD-LDAK Models). The top plot shows results for 14 individual phenotypes (including traits such as height, body mass index, neuroticism and hypertension), while the bottom plot shows averages across all phenotypes.

2021.07.07 | Research news

New methods for predicting complex traits

Doug Speed, together with colleagues from BiRC and NCRR, have recently developed improved methods for predicting complex traits. Their work has this week been published in the journal Nature Communications.

DNA of Icelanders provides new knowledge about extinct human species. Graphics: Astrid Reitzel, AU

2020.04.23 | Research news

Icelandic DNA jigsaw-puzzle brings new knowledge about Neanderthals

An international team of researchers has put together a new image of Neanderthals based on the genes Neanderthals left in the DNA of modern humans when they had children with them about 50,000 years ago. The researchers found the new pieces of the puzzle by trawling the genomes of more than 27,000 Icelanders.

As humans have evolved, those who possess beneficial traits (e.g., are stronger or more intelligent) have been more likely to reproduce, and therefore their genes are more likely to be passed to future generations. This phenomenon is referred to as natural selection. One way to measure the impact of selection is via the parameter alpha; lower alpha implies more selection. The above figure reports estimates of alpha for 14 complex traits, obtained using Doug's new tool. We see strongest evidence for selection for height (often considered a proxy for strength) and college education (a proxy for intelligence).

2020.03.25 | Research news

Evaluating and Improving Heritability Models using Summary Statistics

BiRC member Doug Speed, in collaboration with David Balding and John Holmes (University of Melbourne), has recently developed a new tool that improves our understanding of the genetic factors underlying complex traits. Details of the tool have been published this week in the journal Nature Genetics.

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Thu 19 Aug: 09:00-14:00 | Molslaboratoriet, Ebeltoft
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The 2-day meeting at the Molslab will take place on August 19-20, 2021.

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