APAview

APAview analyzes alternative polyadenylation (APA) features by integrating APA quantification, gene expression, and clinical data to study APA-associated molecular alterations in hematological cancers such as acute promyelocytic leukemia (APL) and acute myeloid leukemia (AML).

Key Features:

• Comprehensive Data Integration: Supports multimodal inputs including APA quantification results from QAPA/DaPars, gene expression datasets, and clinical information.
• Statistical Analyses: Performs correlation analysis, survival analysis, and differential analysis among user-defined groups.
• Customizable Visualizations: Generates customizable visualizations to represent APA metrics and analysis results.
• Cross-disease Applicability: Applies to hematological cancers and other diseases given user-provided experimental data.

Scientific Applications:

• APA dysregulation characterization: Characterizes APA changes associated with pathogenesis in APL and AML.
• Biomarker and target identification: Identifies APA-derived molecular indices that may serve as biomarkers or therapeutic targets.
• Translational integration: Integrates clinical and molecular APA data for translational research and patient outcome studies.

Methodology:

Implemented in Python3 using the Flask framework for backend operations and the Jinja2 templating engine.