scAPA

scAPA analyzes alternative polyadenylation (APA) in single-cell 3' tag RNA sequencing (scRNA-seq) data to detect cell-type-specific APA events.

Key Features:

• Focus on APA: Targets APA events in 3' untranslated regions (3' UTRs) and multiple polyadenylation (pA) sites of mammalian protein-coding genes.
• Single-Cell Resolution: Operates on single-cell 3' tag scRNA-seq data to resolve APA patterns across distinct cell types.
• Data Integration and Analysis: Processes BAM files from the 10x Genomics 3' tag RNA sequencing pipeline and incorporates cell clustering results to map APA modulation.
• Broad Application Scope: Detects widespread APA regulation including global changes in 3' UTR length and increased cleavage at intronic pA sites across datasets.
• Large-Scale Data Utilization: Demonstrates analysis across multiple publicly available scRNA-seq datasets to survey APA across tissues and cell types.

Scientific Applications:

• Gene Regulation Studies: Enables investigation of post-transcriptional regulatory mechanisms mediated by alternative polyadenylation.
• Cell-Type-Specific Insights: Identifies APA variations that distinguish cell types and contribute to cellular diversity and function.
• Biomedical Research: Provides APA-derived information relevant to disease mechanism studies and potential biomarker or therapeutic target discovery.

Methodology:

Processes BAM files from the 10x Genomics 3' tag RNA sequencing pipeline using the shell script "scAPAscript.R" and integrates results from cell clustering analyses.