APAIQ

APAIQ identifies and quantifies polyadenylation sites (PAS) and polyadenylation site usage (PAU) transcriptome-wide from RNA-seq data to characterize alternative polyadenylation (APA) and its impact on mRNA 3' ends.

Key Features:

• PAS identification and PAU quantification: Detects polyadenylation sites (PAS) and quantifies polyadenylation site usage (PAU) from RNA-seq data across the transcriptome.
• High accuracy: Demonstrates superior performance in PAS identification and PAU quantification compared to DaPars2, Aptardi, mountainClimber, SANPolyA, and QAPA.
• Benchmarking with 3' end-seq: Validates APA detection using 3' end-seq data as a benchmark to assess accuracy of identified PAS and quantified PAU.
• Transcriptome-wide analysis: Scans the entire transcriptome to identify APA events and assess their distribution across genes and transcripts.

Scientific Applications:

• Cancer research (example - liver cancer): Applied to 421 RNA-seq samples from liver cancer patients to identify over 540 tumor-associated APA events, supporting discovery of disease-associated regulatory changes and candidate biomarkers or therapeutic targets.

Methodology:

Processes RNA-seq data using robust computational algorithms to pinpoint PAS locations and quantify PAU, with validation against 3' end-seq data and steps to minimize biases and errors reported in previous methods.