research
∙
03/17/2023
A statistical framework for GWAS of high dimensional phenotypes using summary statistics, with application to metabolite GWAS
The recent explosion of genetic and high dimensional biobank and 'omic' ...
share
research
∙
05/24/2022
From differential abundance to mtGWAS: accurate and scalable methodology for metabolomics data with non-ignorable missing observations and latent factors
Metabolomics is the high-throughput study of small molecule metabolites....
research
∙
10/15/2021
A novel framework to quantify uncertainty in peptide-tandem mass spectrum matches with application to nanobody peptide identification
Nanobodies are small antibody fragments derived from camelids that selec...
research
∙
09/23/2020
Factor analysis in high dimensional biological data with dependent observations
Factor analysis is a critical component of high dimensional biological d...
research
∙
09/05/2019
Estimation and inference in metabolomics with non-random missing data and latent factors
High throughput metabolomics data are fraught with both non-ignorable mi...
research
∙
08/17/2018
Estimating and accounting for unobserved covariates in high dimensional correlated data
Many high dimensional and high-throughput biological datasets have compl...
research
∙
01/03/2018
Accounting for unobserved covariates with varying degrees of estimability in high dimensional biological data
An important phenomenon in high dimensional biological data is the prese...
research
∙
01/03/2018
