IRescue

IRescue quantifies transposable element (TE) subfamily expression from single-cell RNA sequencing (scRNA-seq) data to enable analysis of TE transcription at single-cell resolution.

Key Features:

• Subfamily-level quantification: Estimates expression levels of transposable element (TE) subfamilies from scRNA-seq data.
• UMI Deduplication Algorithm: Incorporates a Unique Molecular Identifier (UMI) deduplication algorithm that corrects sequencing errors to improve accuracy of TE expression counts.
• Expectation-Maximization (EM) Procedure: Employs an Expectation-Maximization procedure to redistribute counts of multi-mapping reads across multiple genomic locations or TE subfamilies.
• Precision and Validation: Validated on simulated and real single-cell RNA-seq data, including human colorectal cancer, brain tissue, skin aging studies, and peripheral blood mononuclear cells (PBMCs) during SARS-CoV-2 infection and recovery.

Scientific Applications:

• Cellular Heterogeneity: Quantifies TE expression at single-cell resolution to reveal TE-driven variation within tissues and cell types.
• Disease Progression: Links TE expression patterns to disease states and recovery processes, providing data for potential biomarkers or therapeutic targets in contexts such as cancer and SARS-CoV-2 infection.
• Biological Contextualization: Enables exploration of TE roles across biological conditions, contributing to understanding of their evolutionary impact and functional significance.

Methodology:

IRescue applies UMI deduplication to correct sequencing errors and an Expectation-Maximization (EM) procedure to redistribute multi-mapping read counts to produce subfamily-level TE expression estimates from single-cell RNA-seq data.