John D. Storey

The paper introduces a hypothesis test to detect linkage disequilibrium adjusted for population structure in human datasets.

This paper extends the Transmission Mean Test (TMT) to nuclear families with multiple offspring, enabling detection of genetic loci with causal effects on child phenotypes while accounting for family-specific effects.

This paper introduces a new causal inference method, the transmission mean test (TMT), for identifying genetic loci associated with child phenotypes using parent-child trio data.

The paper introduces a generalized admixture model that accounts for relatedness among admixed populations and shows it can estimate individual-level relatedness.

This paper improves estimation of FST and kinship under complex population structures by introducing a new framework that addresses biases in existing method-of-moments estimators.

The paper extends the optimal discovery procedure (ODP) to handle complex study designs and RNA sequencing, showing improved performance in detecting differentially expressed genes.

This paper extends Hardy-Weinberg equilibrium tests to account for population structure, introducing a new test called structural HWE (sHWE) that automatically selects tuning parameters and identifies structural models.

This paper introduces a generalized FST definition for arbitrary population structures, extending it to account for arbitrary probabilistic dependence among individuals.

The paper introduces new kinship and FST estimators, showing higher genetic differentiation in global human populations compared to existing methods.

The paper introduces superSeq, a method to determine optimal sequencing depth for RNA-Seq studies, finding most studies are undersequenced and saturation depends on statistical methods.

ALStructure estimates population structure using a likelihood-free method that combines principal components analysis with admixture model constraints, outperforming existing methods in accuracy and speed.

The paper introduces a framework to improve false discovery rate estimation using informative variables in genomics applications like eQTL and RNA-seq studies.

This paper develops TeraStructure, a Bayesian inference algorithm for analyzing large-scale genetic variation data, showing improved speed and accuracy on datasets up to 10K individuals.

This paper introduces a new statistical test for genetic associations robust to complex population structure, demonstrating its effectiveness in detecting significant loci in a real-world study.

The paper compares RNA-seq and microarray technologies by analyzing intensity-dependence in gene expression measurements using a controlled yeast experiment.