scTE
scTE quantifies transposable element (TE) expression and chromatin accessibility in single-cell sequencing datasets to reveal TE contributions to cellular heterogeneity and developmental regulation.
Key Features:
- Genome Indexing for Alignment: Builds genome indices that enable rapid alignment of sequencing reads specifically to genes and transposable elements (TEs).
- Single-Cell TE Expression Analysis: Quantifies TE expression at single-cell resolution from single-cell RNA-seq data to profile TE activity across individual cells.
- Dynamic Regulation Insights: Identifies dynamic regulation of specific TE types during processes such as pluripotency reprogramming, differentiation, and embryogenesis, including TEs expressed in subpopulations of embryonic stem cells.
- Expression in Somatic Cells: Detects TE expression in somatic cells, including disease-specific TEs that may be undetectable in bulk analyses.
- Application to Single-Cell ATAC-seq Data: Uses TE chromatin accessibility in single-cell ATAC-seq to discriminate between cell types.
Scientific Applications:
- Exploration of Cell Heterogeneity: Classifies dynamic TE expression patterns across single cells to investigate contributions of TEs to cellular heterogeneity.
- Developmental Biology Studies: Tracks TE expression and regulation during embryogenesis and stem cell differentiation to study developmental processes.
- Disease Research: Identifies disease-associated TEs in single cells to support investigations of molecular mechanisms in disease contexts.
Methodology:
Builds genome indices and aligns sequencing reads specifically to genes and TEs; processes single-cell sequencing data with emphasis on TE expression; integrates genome indexing and alignment techniques optimized for both gene-centric and TE-centric analyses; applies TE chromatin accessibility analysis to single-cell ATAC-seq data.
Topics
Details
- License:
- MIT
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- Python
- Added:
- 7/18/2024
- Last Updated:
- 11/24/2024
Operations
Publications
He J, Babarinde IA, Sun L, Xu S, Chen R, Shi J, Wei Y, Li Y, Ma G, Zhuang Q, Hutchins AP, Chen J. Identifying transposable element expression dynamics and heterogeneity during development at the single-cell level with a processing pipeline scTE. Nature Communications. 2021;12(1). doi:10.1038/s41467-021-21808-x. PMID:33674594. PMCID:PMC7935913.
Downloads
- Downloads pageVersion: v1.0.0https://github.com/JiekaiLab/scTE/releases/tag/scTE.v1.0.0
- Software packagehttps://anaconda.org/bioconda/scte