Robin J. Hofmeister

Evaluating anonymized genome re-identification using polygenic predictions and its implications for data privacy

This paper evaluates the feasibility of re-identifying individuals using polygenic predictions and finds that real-world effectiveness is limited due to low priors and poor sensitivity for sensitive genotypes.

Detecting CYP2C19 deletions from genotyping array signals using neural networks

This paper develops a neural network model, nnCNV, to detect CYP2C19 deletions from genotyping array signals, achieving higher accuracy than existing methods.

Mapping corpus callosum architecture: developmental, genetic, and cognitive correlates in youth

This study characterizes spatial variation in corpus callosum structure and its developmental, genetic, and cognitive correlates using multimodal data from youth.

Separating direct, indirect and parent-of-origin genetic effects in the human population

The paper introduces JODIE, a model to estimate direct, indirect, and parent-of-origin genetic effects on height, BMI, and educational attainment using family trios from two biobanks.

Sex differences in the genetic basis of human recombination within 190,000 parent-child pairs

This study identifies 58 genomic regions associated with meiotic recombination, 24 of which are sex-specific, and finds a moderate genetic correlation between male and female recombination rates.

Parental haplotypes reconstruction in up to 440,209 individuals reveals recent assortative mating dynamics

The paper estimates genetic assortative mating using haplotype reconstruction in large biobank cohorts, revealing recent trends in mate choice and its genetic impact.

Compounding of rare pathogenic copy-number variants and polygenic background is consistent with assortative mating.

The paper investigates how polygenic scores and copy-number variants interact, finding that assortative mating explains their positive correlation and contributes to genetic risk compounding.

Parent-of-Origin inference and its role in the genetic architecture of complex traits: evidence from ~265,000 individuals

The paper infers parent-of-origin effects in ~265,000 individuals using a novel method, identifying over 30 novel POEs and confirming known associations, supporting the parental conflict hypothesis.

Yield of genetic association signals from genomes, exomes, and imputation in the UK biobank

The paper compares the effectiveness of whole genome sequencing, whole exome sequencing with imputation, and array genotyping in detecting genetic associations across 100 complex traits in the UK Biobank, finding that WES+IMP provides similar signal yield to WGS with greater efficiency.

Improving population scale statistical phasing with whole-genome sequencing data

This paper introduces SAPPHIRE, a method that improves haplotype phasing accuracy using whole-genome sequencing data by refining phase calls with read-level information.

Imputation of low-coverage sequencing data from 150,119 UK Biobank genomes

The paper introduces GLIMPSE v2.0.0, a scalable imputation method for low-coverage genomes, reducing computational costs while maintaining high accuracy for rare variants and low-coverage samples.

Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank

This paper introduces SHAPEIT5, a phasing method that accurately phases rare variants in UK Biobank WGS and WES data, improving imputation accuracy and identifying gene essentiality through compound heterozygous events.

Parent-of-origin effects in the UK Biobank

The paper infers parent-of-origin effects in the UK Biobank using a novel probabilistic method, identifying 101 significant associations across 59 biomarkers and 38 phenotypes.

The molecular basis, genetic control and pleiotropic effects of local gene co-expression

The paper identifies local gene co-expression patterns across human tissues and links them to eQTLs associated with multiple traits.

Efficient phasing and imputation of low-coverage sequencing data using large reference panels

This study introduces GLIMPSE, a method for efficient phasing and imputation of low-coverage sequencing data, showing improved accuracy and cost-effectiveness compared to existing methods.