LRT: T Cell Trajectory Inference by Integrative Analysis of Single-Cell TCR-seq and RNA-seq data

Abstract

Single-cell RNA sequencing (scRNA-seq) data has been widely used for cell trajectory inference, with the assumption that cells with similar expression profiles share the same differentiation state. However, the inferred trajectory may not reflect true clonal relationships among cells. Single cell T cell receptor sequencing (scTCR-seq) data provides invaluable insights into the clonal relationship among cells, yet it lacks the functional characteristics. Therefore, scRNA-seq and scTCR-seq data complement each other in improving the trajectory inference. However, very limited computational efforts have been devoted to the integration of scRNA-seq and scTCR-seq data for cell trajectory inference. To address this gap, we developed LRT, an R package for the integrative analysis of scTCR-seq and scRNA-seq data for T cell trajectory inference. In addition, it provides two Shiny apps that allow users to interactively explore distributions of clonotypes and implement clustering of cell trajectories. We illustrated its utility using scRNA-seq and scTCR-seq data of CD4+ T cells with acute lymphocytic choriomeningitis virus infection.