PRADA

PRADA analyzes paired-end RNA-seq data to quantify gene expression, detect supervised and unsupervised fusion transcripts including intragenic fusion variants, compute homology scores, and classify fusion frames to support identification of genetic alterations in cancer genomics.

Key Features:

• Paired-end RNA-seq processing: Processes raw paired-end RNA-seq data to produce gene expression measurements and quality metrics.
• Detection of fusion transcripts: Identifies both unsupervised and supervised fusion transcripts from RNA-seq data.
• Intragenic fusion variant detection: Detects intragenic fusion variants within individual genes.
• Homology scoring and fusion frame classification: Computes homology scores and classifies fusion frames for detected fusion events.
• Dual-mapping strategy: Employs a dual-mapping strategy to enhance sensitivity and refine analytical endpoints.
• Modular design and scalability: Implements a modular pipeline architecture to accommodate large-scale RNA-seq datasets.

Scientific Applications:

• TCGA glioblastoma analyses: Applied to The Cancer Genome Atlas glioblastoma projects for detection of fusion events and expression profiling.
• TCGA renal clear cell carcinoma analyses: Applied to The Cancer Genome Atlas renal clear cell carcinoma projects for detection of fusion events and expression profiling.

Methodology:

Modular pipeline design; dual-mapping strategy; detection of supervised and unsupervised fusion transcripts; identification of intragenic fusion variants; computation of homology scores; classification of fusion frames.