Pier Francesco Palamara

This paper introduces GhostBuster, a method to detect unsampled admixture events in human history using genome-wide genealogies, revealing multiple back-to-Africa migrations and deep ancestral lineages.

The paper analyzes DNA repeat instability in 700,000 participants to identify genetic modifiers of repeat expansion and contraction rates and their clinical associations.

The paper introduces ARG-RHE, a method to estimate heritability and perform association testing using ancestral recombination graphs, showing improved results over imputation alone.

This paper introduces FLEX, a method for estimating gene-level heritability from whole-exome sequencing data, showing rare coding variants contribute significantly to complex trait heritability.

This paper uses ancient DNA data to trace the genetic origins of the Yamnaya culture and links their expansion to the spread of Indo-European languages.

The paper introduces Threads, a method for efficiently inferring ancestral recombination graphs from large genomic datasets, improving imputation accuracy and trait association detection.

This paper builds a haplotype reference panel from Genomics England data and imputes UK Biobank data, revealing more rare variants and suggesting limitations in detecting rare variant associations with current sample sizes.

HapNe infers recent effective population size variation in modern and ancient DNA samples using IBD or LD, showing improved accuracy and efficiency.

HAPNEST generates and evaluates large-scale synthetic genotype and phenotype datasets for polygenic risk score analysis.

This study analyzes ancient DNA from LBK Neolithic sites to show genetic differences between eastern and western LBK populations, with evidence of patrilocality and no evidence of male-biased WHG admixture.

The paper introduces a method to infer genealogies from biobank-scale data and uses them in mixed models to detect associations with complex traits, finding more rare variants than traditional imputation methods.

The paper detects identity-by-descent segments in 487,409 UK Biobank samples to reveal population structure, evolutionary history, and trait associations.

The paper quantifies frequency-dependent genetic architectures and negative selection effects across 25 UK Biobank traits using a statistical model and imputed genotypes.

The paper introduces a method to detect directional effects of transcription factor binding on disease risk using GWAS data and applies it to identify new causal genes and mechanisms.

The paper develops ASMC, a fast method to estimate coalescence times from SNP data, detects selection signals and finds enrichment of disease heritability in regions of background selection.

The paper quantifies linkage disequilibrium (LD) dependent architecture of complex traits, finding that low LD SNPs have higher heritability, likely due to negative selection.

The paper quantifies human mutation and gene conversion rates using IBD segments and population history, finding higher mutation rates than pedigree-based estimates but lower than primate substitution rates.