Oarfish

Oarfish quantifies transcript abundance from long-read sequencing data using a probabilistic model that incorporates a novel coverage score to improve the conditional probability of fragment assignment.

Key Features:

• Coverage Score Integration: Incorporates a novel coverage score into the probabilistic model to improve the conditional probability of fragment assignment.
• Long-Read Optimization: Tailored quantification for long-read sequencing data, addressing challenges from lower throughput and technical artifacts compared to short-read technologies.
• Primary Isoform Accuracy: Produces more accurate quantification estimates for primary isoforms present in specific cell lines or tissue types.

Scientific Applications:

• Transcriptome Quantification: Estimates transcript abundance from full-length isoform long-read sequencing data.
• Isoform-Level Analysis: Enables accurate quantification of transcript isoforms in cell line or tissue-specific contexts.

Methodology:

Oarfish uses a probabilistic model where a novel coverage score affects the conditional probability of fragment assignment.