stAPAminer

stAPAminer mines spatial patterns of alternative polyadenylation (APA) from spatially barcoded spatial transcriptomics (ST) data to identify and quantify APA sites and reveal their spatial usage dynamics.

Key Features:

• Identification and Quantification of APA Sites: Identifies and quantifies APA sites from spatially barcoded ST data.
• Imputation Model for Signal Recovery: Implements an imputation model based on the k-nearest neighbors algorithm to enhance recovery of APA signals.
• Spatial Pattern Analysis: Detects genes exhibiting spatial patterns of APA usage variation across tissue regions and morphological layers.
• Reproducibility Across Replicates: Analyzes multiple ST replicates to assess the reproducibility of spatial APA patterns for genes.

Scientific Applications:

• Spatial Transcriptomic Studies: Enables investigation of how APA contributes to gene expression regulation within spatial transcriptomic atlases generated by ST technologies.
• Morphological Layer Analysis: Applied to mouse olfactory bulb (MOB) ST data to reveal spatial APA usage across morphological layers.
• Gene Dynamics Exploration: Compiles lists of genes with spatial APA dynamics to characterize major spatial expression patterns across tissue regions.

Methodology:

Processes spatially barcoded ST data to identify and quantify APA sites, employs an imputation model based on the k-nearest neighbors algorithm to recover APA signals, identifies genes with spatial patterns of APA usage variation, and compares patterns across multiple ST replicates to evaluate reproducibility.