Yingtian Hu

Impact of experimental bias on compositional analysis of microbiome data

This paper evaluates how experimental bias affects microbiome compositional analysis and shows that LOCOM is robust to both main and interaction biases compared to other methods.

LOCOM: A logistic regression model for testing differential abundance in compositional microbiome data with false discovery rate control

LOCOM is a logistic regression method for differential abundance testing in microbiome data that controls FDR and is robust to experimental biases.

Testing microbiome associations with censored survival outcomes at both the community and individual taxon levels

The paper develops new statistical methods to test microbiome associations with censored survival outcomes at both community and individual taxon levels, showing improved performance over existing methods.