Jerome Kelleher

This paper introduces SMC(k), a tunable approximation of the Coalescent with Recombination, showing it balances computational efficiency and accuracy in simulating Ancestral Recombination Graphs.

The paper develops a method to estimate variance components and predict genetic values using ancestral recombination graphs (ARGs) and linear mixed models on large datasets.

The paper develops a scalable method to estimate allele ages from large genomic datasets, revealing purifying selection and heterogeneity in ultra-rare variants.

This paper introduces branch relatedness and efficient algorithms for computing branch GRMs using tree sequences, enabling large-scale genomic analysis.

The paper extends the stdpopsim simulation framework to include realistic selection models, enabling studies of selection's impact on genetic variation across species.

The paper introduces a method to insert non-coalescing haplotypes into ancestral recombination graphs (ARGs) and proposes new metrics to compare ARGs based on haplotype relationships.

tsbrowse is an open-source web tool for interactive visualization of Ancestral Recombination Graphs, enabling exploration of genetic ancestry data.

This paper develops a framework to detect and quantify sexual reproduction in populations by addressing biases in genomic data analysis, using ancestral recombination graphs and simulation models.

This paper presents a backwards-time formulation of the Sequentially Markov Coalescent (SMC) and derives a likelihood definition for a general class of Ancestral Recombination Graphs (ARGs) without requiring precise recombination event details.

This paper improves demographic and evolutionary parameter estimation by using ARG-derived IBD segments without length thresholds, reducing computation time while maintaining statistical efficiency.

The paper introduces VCF Zarr, a format for efficiently storing and processing large-scale genetic variation data, demonstrating improved performance and scalability over traditional VCF formats.

The paper introduces a new formalism for representing ancestral recombination graphs that generalizes classical approaches and supports modern computational methods.

tstrait simulates quantitative traits on ancestral recombination graphs to enable efficient GWAS applications without losing ancestral information.

The paper models French Canadian ancestry using genealogical and genetic data, revealing population structure shaped by geography and migration.

The paper expands the stdpopsim species catalog and improves genome simulations by adding non-crossover recombination and species-specific annotations, making simulations more realistic for non-model organisms.

The paper introduces an algorithm to efficiently simulate local ancestry tracts from tree sequences, implemented in tskit and tspop.

The paper introduces Demes, a standard format for demographic models in population genetics to improve clarity and ease of use in simulations and analysis.

This paper introduces a non-parametric method to infer human genealogical history from modern and ancient genomes, demonstrating its ability to reconstruct relationships and identify descendants of ancient samples.

The paper introduces msprime 1.0, a high-performance simulation tool for ancestry and mutation in population genetics, showing it is faster and more memory efficient than existing alternatives.

The paper identifies and discusses two bugs in population genetic models implemented with msprime, highlighting their impact on published analyses and offering recommendations to prevent similar errors.

The paper introduces a framework to efficiently compute population genetic statistics using genealogical trees, showing significant computational improvements over traditional methods.

This paper introduces an efficient method for recording and simplifying genetic history in population genetics simulations, reducing storage and computational costs.

Bioconda provides a sustainable, comprehensive distribution of bioinformatics software using Conda for reproducible analysis across platforms.

This paper introduces genome graphs as an alternative to linear reference genomes, showing they improve read mapping and variant calling compared to the standard GRCh38 reference.

The paper introduces efficient methods for coalescent simulation and genealogical analysis that scale to large sample sizes and improve speed and storage efficiency.