activity
20112021
most citedA functional data analysis approach for genetic association studies

38 citations · 111 across the 14 of their papers we have counts for

collaborators

15 papers

stat.ME2021

Dynamic Gene Coexpression Analysis with Correlation Modeling

Tae Hyun Kim, Dan Nicolae

In many transcriptomic studies, the correlation of genes might fluctuate with quantitative factors such as genetic ancestry. We propose a method that models the covariance between…

cs.LG2021★ 17 cited

VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments

Lizhen Nie, Mao Ye, Qiang Liu +1

Motivated by the rising abundance of observational data with continuous treatments, we investigate the problem of estimating the average dose-response curve (ADRF). Available param…

stat.ME2021★ 1 cited

Weighted-Graph-Based Change Point Detection

Lizhen Nie, Dan L. Nicolae

We consider the detection and localization of change points in the distribution of an offline sequence of observations. Based on a nonparametric framework that uses a similarity gr…

stat.ME2019★ 2 cited

Estimation and inference in metabolomics with non-random missing data and latent factors

Chris McKennan, Carole Ober, Dan Nicolae

High throughput metabolomics data are fraught with both non-ignorable missing observations and unobserved factors that influence a metabolite's measured concentration, and it is we…

stat.ME2018★ 3 cited

Estimating and accounting for unobserved covariates in high dimensional correlated data

Chris McKennan, Dan Nicolae

Many high dimensional and high-throughput biological datasets have complex sample correlation structures, which include longitudinal and multiple tissue data, as well as data with…

stat.ME2018

Identifying Heritable Communities of Microbiome by Root-Unifrac and Wishart Distribution

Yunfan Tang, Dan Nicolae

We introduce a method to identify heritable microbiome communities when the input is a pairwise dissimilarity matrix among all samples. Current methods target each taxon individual…