Research in Progress: Rising Star Seminar

Li Song, PhD, assistant professor at Dartmouth, will present computational methods for comprehensive immune receptor and microbiome analysis from standard sequencing data. Sequencing data contains rich immune and microbiome information, but common RNA-seq workflows rely heavily on reference genomes and miss underrepresented features such as immune receptors and microbes. Song will discuss TRUST4, which reconstructs T-cell receptor (TCR) and B-cell receptor (BCR) sequences from bulk and single-cell RNA-seq data, and T1K, for genotyping highly polymorphic genes such as killer immunoglobulin-like receptors (KIRs) and human leukocyte antigen (HLA) genes. She will also introduce Centrifuger, a taxonomic classification tool using a novel run-block compression scheme to store massive microbial genome databases efficiently. Centrifuger enables accurate species-level classification and reveals microbiome composition. These tools expand the scope of low-cost sequencing data, enabling integrated immune and microbiome insights.