SCAFE

SCAFE analyzes single-cell 5′ end RNA sequencing (sc-end5-seq) data to profile transcribed cis-regulatory elements (tCREs) such as promoters and enhancers and to quantify gene expression and enhancer activity for cell-type and cell-state-specific gene regulation studies.

Key Features:

• sc-end5-seq processing: Processes and analyzes single-cell 5′ end RNA sequencing (sc-end5-seq) data to detect transcription initiation at regulatory elements.
• tCRE detection: Detects transcribed cis-regulatory elements (tCREs), including promoters and enhancers, from sc-end5-seq reads.
• Simultaneous quantification: Quantifies gene expression and enhancer activities within the same assay to enable joint analysis of transcript and regulatory activity.
• Priming support: Supports both random priming and oligo(dT) priming techniques to detect enhancer RNAs (eRNAs).
• genuine tCRE identification: Identifies genuine tCREs and analyzes their transcriptional activities across cells.
• co-activity-based interaction prediction: Uses co-activity of tCREs to predict CRE interactions and contrasts these predictions with approaches based on chromatin accessibility (aCRE) data.
• Sensitivity to promoter usage shifts: Detects shifts in alternative promoter usage with increased sensitivity compared to accessible CRE (aCRE) methods.
• Disease heritability enrichment: Associates tCREs with higher enrichment in disease heritability relative to aCRE-based annotations.

Scientific Applications:

• CRE profiling: Profiling promoters and enhancers at single-cell resolution to map transcribed regulatory elements.
• Gene regulation analysis: Investigating cell-type and cell-state-specific gene regulation by jointly analyzing expression and enhancer activity.
• Enhancer RNA studies: Detecting and quantifying enhancer RNAs (eRNAs) using random or oligo(dT) priming strategies.
• CRE interaction inference: Predicting CRE interactions based on co-activity patterns of tCREs.
• Alternative promoter usage: Detecting shifts in alternative promoter usage across cells and conditions.
• Disease genetics: Linking transcribed regulatory elements to disease heritability and genetic predisposition analyses.

Methodology:

Processes sc-end5-seq reads to detect transcription initiation sites and transcribed CREs; supports random and oligo(dT) priming for enhancer RNA detection; identifies genuine tCREs and quantifies their activities; predicts CRE interactions based on co-activity and contrasts results with chromatin accessibility (aCRE)-based approaches.