Huilin Li

Vritra: gene-specific reference construction for species-resolved functional profiling of metagenomic and metatranscriptomic data

Vritra constructs gene-specific references for metagenomic and metatranscriptomic data to enable species-resolved functional profiling and uncover gene-taxa associations.

Joint Modeling of Longitudinal Biomarker and Survival Outcomes with the Presence of Competing Risk in Nested Case-Control Studies with Application to the TEDDY Microbiome Dataset

The paper introduces JM-NCC, a joint modeling framework for nested case-control studies with competing risks, applied to the TEDDY microbiome dataset to analyze biomarker and survival outcomes.

IFNγ-Driven Inflammatory Responses in the Nasal Mucosa Drive Influenza Virus Shedding and Transmission

This study shows that IFNγ-driven inflammation in the nasal mucosa increases influenza virus shedding and transmission, linking infectiousness to host immune responses rather than viral replication alone.

An integrated strain-level analytic pipeline utilizing longitudinal metagenomic data

LongStrain improves strain-level analysis in longitudinal metagenomic data by jointly modeling strain proportions and genomic variants, outperforming existing methods in variant calling and proportion estimation.

ARZIMM: A Novel Analytic Platform for the Inference of Microbial Interactions and Community Stability from Longitudinal Microbiome Study

ARZIMM infers microbial interactions and community stability from longitudinal microbiome data using a zero-inflated mixed-effects model.

Microbial trend analysis for common dynamic trend, group comparison and classification in longitudinal microbiome study

The paper introduces a microbial trend analysis framework to characterize dynamic microbial patterns in longitudinal studies, showing its effectiveness in trend detection, group comparison, and classification.

Joint Modeling of Zero-inflated Longitudinal Proportions and Time-to-event Data with Application to a Gut Microbiome Study

The paper introduces JointMM, a joint modeling framework for analyzing longitudinal microbiome proportions and time-to-event data, showing its effectiveness in identifying microbial associations with disease progression.

Estimating and testing the microbial causal mediation effect with high-dimensional and compositional microbiome data

The paper introduces a causal mediation model for high-dimensional microbiome data to estimate and test microbial causal effects in a three-factor study design.

q2-longitudinal: a QIIME 2 plugin for longitudinal and paired-sample analyses of microbiome data

The paper introduces q2-longitudinal, a QIIME 2 plugin for analyzing longitudinal and paired microbiome data, offering methods like linear mixed effects models and volatility analysis.