Jean Morrison

This paper uses multivariable Mendelian randomization to assess the causal effects of CRP on diseases while adjusting for heritable confounders, finding significant effects only on rheumatoid arthritis and schizophrenia.

This paper introduces INTERFACE, a probabilistic fine-mapping method that improves the identification of causal genes by integrating colocalization and transcriptome-wide association evidence.

GWASBrewer simulates realistic GWAS summary statistics efficiently, enabling evaluation of statistical methods without individual-level data.

The paper argues that causal gene identification methods should be evaluated using statistical techniques instead of gold-standard gene sets due to their incompleteness and labeling biases.

This study identifies 31 plasma proteins and expands genetic loci associated with PCOS, highlighting metabolic and hormonal influences and polygenic risk effects on cardio-metabolic outcomes.

The paper introduces Multi-INTACT, a method that integrates transcriptome-wide association studies with protein QTL data to identify causal genes for metabolites, finding that both gene products are relevant for most gene nominations.

This paper introduces a probabilistic framework to integrate TWAS and colocalization analysis, improving gene implication and pathway identification for complex traits.

This study identifies 303 novel genetic signals associated with plasma metabolites in Finnish men, revealing biological insights into disease mechanisms.

The paper integrates GWAS data with functional genomic annotations of decidual stromal cells to identify loci and target genes associated with gestational duration and preterm birth.

This paper introduces a new Mendelian randomization method, CAUSE, that accounts for correlated and uncorrelated pleiotropic effects, showing improved robustness in detecting true causal relationships.

This paper introduces a statistical framework to identify risk genes from de novo mutations in whole-genome sequencing studies, finding new autism risk genes.