LRT

LRT performs integrative analysis of single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq) data to explore clonal differentiation trajectory heterogeneity in immune cells such as CD8+ and CD4+ T cells.

Key Features:

• Integrative analysis: Combines scRNA-seq transcriptomic profiles with scTCR-seq clonotype information to link gene expression states with T cell clonal identity.
• Trajectory inference: Constructs cell differentiation trajectories from scRNA-seq transcriptomic data and refines them using TCR sequence and phenotype information.
• Clonotype clustering: Identifies clusters of cells sharing clonotypes to reveal clonal groupings and their differentiation patterns.
• Trajectory biasedness evaluation: Assesses the distribution of clonotype clusters along inferred trajectories to detect skewed differentiation biases.
• Clonotype cluster characterization: Analyzes cluster properties including expansion capability, V-J gene usage, and CDR3 motifs.

Scientific Applications:

• T cell differentiation studies: Dissects heterogeneity of CD8+ and CD4+ T cell differentiation by linking clonal identity to transcriptomic trajectories.
• Clonal expansion and immune memory analysis: Evaluates clonotype expansion and repertoire features relevant to immune memory formation.
• Infection and adaptive response profiling: Investigates clonal and transcriptional dynamics during infections such as acute lymphocytic choriomeningitis virus (LCMV).

Methodology:

Explicit computational steps include preprocessing of single-cell data; cell trajectory inference using scRNA-seq transcriptomes; clonotype clustering from scTCR-seq data; trajectory biasedness evaluation of clonotype clusters; and clonotype cluster characterization including expansion, V-J gene usage, and CDR3 motif analysis.