Nathan LaPierre

The paper integrates perturbational screens, eQTL, and GWAS data to identify mediating genes for complex traits, finding 546 significant genes enriched for immune response and cellular signaling.

The paper identifies genetic loci associated with saline self-administration in mice, finding distinct genetic bases compared to cocaine self-administration.

The paper identifies causal genes at QTLs associated with fear-related behavior using complementation testing and finds six genes, including four with known synaptic roles and one long non-coding RNA.

This study shows that accounting for isoform expression in eQTL mapping increases power and highlights issues with current methods in real data.

This study investigates the genetic basis of dietary iron overload and associated pathologies in mice using the Hybrid Mouse Diversity Panel, identifying genetic loci and pathways involved.

This paper introduces MR-Twin, a Mendelian Randomization method robust to population stratification, and shows it reduces false positives compared to standard methods in UK Biobank data.

The paper identifies genetic loci and pathways associated with cocaine self-administration in mice using GWAS and TWAS, highlighting Trpv2 as a key gene.

The paper evaluates metagenomic software tools using realistic datasets, highlighting improvements in assembly and taxon profiling while identifying remaining challenges in virus/archaea detection and reproducibility.

This paper introduces sensitivity analysis tools for Mendelian randomization to assess robustness against population stratification, batch effects, and horizontal pleiotropy.

This paper introduces MsCAVIAR, a method for fine mapping causal variants across multiple GWAS studies, showing it reduces causal set sizes by over 20% in Type 2 Diabetes analysis.

Metalign improves metagenomic profiling by using containment min hash for efficient alignment-based analysis, achieving better results than existing methods on benchmark datasets.

MiCoP improves microbial community profiling by accurately detecting viral and fungal organisms in metagenomic samples using a comprehensive reference database.

MiniScrub improves Nanopore read quality through de novo error correction, leading to better genome assembly with fewer misassemblies and indel errors.