Daxi Wang

STID provides a standardized framework for analyzing spatial transcriptomic data in infectious diseases, enabling pathogen background correction, niche identification, and multi-sample comparative analyses.

The paper analyzes the pathogen infectome of small mammals in southern China, identifying new pathogens and factors influencing their distribution and diversity.

The paper compares single-cell transcriptomic data of lung tissues from bats, cats, tigers, and pangolins to analyze viral receptor distribution and immune responses to respiratory viruses.

This study characterizes intra-host SARS-CoV-2 genomic variants and their evolutionary dynamics in COVID-19 patients using deep sequencing data.

This study compares SARS-CoV-2 viral populations in COVID-19 patients to show narrow transmission bottlenecks and stochastic dynamics in intra-host and inter-host evolution.

The paper identifies CTP synthesis as a metabolic bottleneck that constrains SARS-CoV-2 evolution towards attenuation and highlights viperin's role in antiviral defense.

This paper compares amplicon, hybrid capture, and metatranscriptomic sequencing methods for directly sequencing SARS-CoV-2 genomes from clinical samples, finding differences in bias, sensitivity, and accuracy.