15 citations · 18 across the 6 of their papers we have counts for
6 papers
Principal Amalgamation Analysis for Microbiome Data
Yan Li, Gen Li, Kun Chen
In recent years microbiome studies have become increasingly prevalent and large-scale. Through high-throughput sequencing technologies and well-established analytical pipelines, re…
It's All Relative: New Regression Paradigm for Microbiome Compositional Data
Gen Li, Yan Li, Kun Chen
Microbiome data are complex in nature, involving high dimensionality, compositionally, zero inflation, and taxonomic hierarchy. Compositional data reside in a simplex that does not…
The More Data, the Better? Demystifying Deletion-Based Methods in Linear Regression with Missing Data
Tianchen Xu, Kun Chen, Gen Li
We compare two deletion-based methods for dealing with the problem of missing observations in linear regression analysis. One is the complete-case analysis (CC, or listwise deletio…
Multivariate Log-Contrast Regression with Sub-Compositional Predictors: Testing the Association Between Preterm Infants' Gut Microbiome and Neurobehavioral Outcomes
Xiaokang Liu, Xiaomei Cong, Gen Li +2
The so-called gut-brain axis has stimulated extensive research on microbiomes. One focus is to assess the association between certain clinical outcomes and the relative abundances…
Integrative Multi-View Reduced-Rank Regression: Bridging Group-Sparse and Low-Rank Models
Gen Li, Xiaokang Liu, Kun Chen
Multi-view data have been routinely collected in various fields of science and engineering. A general problem is to study the predictive association between multivariate responses…
A General Framework for Association Analysis of Heterogeneous Data
Gen Li, Irina Gaynanova
Multivariate association analysis is of primary interest in many applications. Despite the prevalence of high-dimensional and non-Gaussian data (such as count-valued or binary), mo…