gmafrafortuna_quangen_tree

Ancestral Recombination Graphs (ARGs) are being used in population and human genetics to efficiently represent, store, and analyse large-scale whole-genome sequence data. ARG provide a comprehensive way to represent DNA inheritance and variation in sample of genomes via past coalescence, mutation and recombination events. A single ARG describe the genealogical history of an entire genome, but can be decomposed into local trees. Local trees represent the history of DNA variation at specific genomic positions, delimited by recombination events. The development of quantitative genetic methods to work with ARGs and phenotypes is an active area of research.

In this work we study how a tree-based model can be used to understand and estimate rare and drifting mutation effects in a genome sequence context. We demonstrate the theory proposed in [PAPER] with:

A walk-through small example

comparing the proposed TBLUP method with standard SNP- and GBLUP

simulations/small_example/concept_mut_effect.R

A simulation study based on the tree of mitochondrial DNA (mtDNA) from the 1000 Bull Genomes Project data

Here we consider multiple scenarios for mutation effects and study how well they can be estimated.

simulations/simulated_data/inla_models.R

An application of the model to a real mtDNA and phenotypes dataset from Brajkovic et al. (2024).

real_data/RScripts/arg_real_phenotypes.R

We provide the inferred tree sequences and derived tables required to reproduce the analyses. Scripts for generating these data is also available.