AIDD

AIDD analyzes RNA-seq datasets to characterize transcriptome diversity driven by alternative splicing and post-transcriptional RNA editing, including ADAR and APOBEC activities.

Key Features:

• Comprehensive Analysis: Integrates open-source tools within a static VirtualBox environment to provide a reproducible computational setup.
• Automated Workflow: Automates processing from raw FASTQ RNA-seq data to publication-ready results and figures via scripts that perform format conversions.
• RNA Editing Detection: Maps RNA editing events at global and local scales and identifies ADAR (adenosine deaminases acting on RNA) and APOBEC editing sites.
• Alternative Splicing Analysis: Detects alternative splicing events contributing to transcriptome diversity.
• Visualization: Generates publication-ready visualizations of ADAR editing landscapes and ADAR isoform diversity related to innate immunity and viral infections.
• Time-series Analysis: Implements Guttman scale pattern analysis for time-series RNA editing studies.
• Variant Calling: Supports high-throughput variant calling on large RNA-seq datasets.

Scientific Applications:

• Transcriptome-wide RNA editing inference: Enables inference of RNA editing patterns across the transcriptome, including longitudinal analyses using Guttman scale patterns.
• Disease and infection studies: Applied to RNA-seq from Zika virus–infected neural progenitor cells to investigate ADAR editing dysregulation associated with congenital Zika syndrome.

Methodology:

Integration of open-source tools within a static VirtualBox image; automated processing from raw FASTQ RNA-seq files to publication-ready results and figures via scripts for format conversions; mapping of RNA editing events and identification of ADAR/APOBEC sites; high-throughput variant calling and Guttman scale pattern analysis for time-series data.