Nicholas Mancuso, PhD
Assistant Professor of Population and Public Health Sciences
Biography
My research aims to develop novel computational and statistical approaches to understand the genetic etiology of complex diseases. This includes integrating molecular phenotypes (e.g., gene expression, protein abundance) with large-scale genome-wide association studies, characterizing the genetic architecture of complex disease (e.g., rare vs common variation), and quantifying the role of selection in shaping the effect-size distribution for alleles.
Publications
twas_sim, a Python-based tool for simulation and power analysis of transcriptome-wide association analysis.
Bioinformatics. 2023 May 4;39(5). doi: 10.1093/bioinformatics/btad288. PubMed PMID: 37099718; PubMed Central PMCID: PMC10172036.
Genome-Wide Analyses Characterize Shared Heritability Among Cancers and Identify Novel Cancer Susceptibility Regions.
J Natl Cancer Inst. 2023 Mar 17;. doi: 10.1093/jnci/djad043. Epub 2023 Mar 17. PubMed PMID: 36929942;
Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics.
bioRxiv. 2023 Apr 18;. doi: 10.1101/2023.04.10.536252. Epub 2023 Apr 18. PubMed PMID: 37131817; PubMed Central PMCID: PMC10153181.
A scalable variational approach to characterize pleiotropic components across thousands of human diseases and complex traits using GWAS summary statistics.
medRxiv. 2023 Mar 29;. doi: 10.1101/2023.03.27.23287801. Epub 2023 Mar 29. PubMed PMID: 37034739; PubMed Central PMCID: PMC10081403.
Novel insight into the etiology of ischemic stroke gained by integrative transcriptome-wide association study.
medRxiv. 2023 Mar 31;. doi: 10.1101/2023.03.30.23287918. Epub 2023 Mar 31. PubMed PMID: 37034585; PubMed Central PMCID: PMC10081428.
Courses Taught
- Statistical Methods in Human Genetics