RNAseqEval

RNAseqEval evaluates splice-aware RNA-seq alignments for long-read sequencing data from Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) by assessing alignment accuracy, resource usage, and effects of error correction.

Key Features:

• Splice-Aware Alignment Benchmarking: Quantifies alignment quality of RNA-seq aligners on synthetic and real PacBio and ONT MinION datasets using metrics against simulated genomic origins or annotated transcripts.
• Error Correction and Resource Analysis: Assesses the impact of self-correction and short-read–assisted error correction on alignment accuracy and reports computational resource usage across aligners.

Scientific Applications:

• Long-Read RNA-Seq Workflow Optimization: Supports benchmarking and selection of splice-aware aligners for high-error-rate long-read transcriptomics in genetic research and diagnostics.

Methodology:

RNAseqEval compares splice-aware aligners on PacBio and ONT datasets by computing alignment quality metrics relative to known genomic or transcript annotations, evaluating performance before and after error correction, and measuring computational resource consumption.