bioRxivBioinformaticsPreprint
PeakLocus: A transcript-aware toolkit for RNA-Centric Genomic Annotation
George Boateng-SarfoiD, Shashank PritamiD, Sarah A. SignoriD
Abstract
Annotating genomic coordinates is an important step for identifying where along the transcript genomic features are enriched yet many widely used peak annotation tools were designed primarily around general genomic or chromatin features. We developed PeakLocus, a dependency-free Java command line tool that assigns RNA feature to transcript interval in an explicitly RNA centered transcript context. PeakLocus accepts bed-like and tabular interval files together with a gene transfer file as reference, detects coordinates and strand structure, and reports gene, transcript, biotype, and location information such as 5' UTR, 3' UTR, CDS. Generic UTR features are resolved using transcript-specific CDS boundaries and strand, while introns are derived from transcript exon structure. We benchmarked PeakLocus against BEDTools, UROPA, ChIPseeker, and HOMER using 466,526 evaluable RNA-associated peaks from 27 Drosophila, mouse, and human datasets and a balanced reference-derived benchmark of 30,000 fixed-width intervals. On real-world data, PeakLocus assigned a strict RNA-location category to 92.8% of evaluable intervals and showed 99.5% concordance with a direct BEDTools-derived overlap baseline among jointly annotated peaks. In the controlled benchmark, PeakLocus achieved 86.4% exact five-class recovery overall, with 99.9% recovery in mouse and 99.6% in human. Comparator differences were strongly influenced by native annotation ontology, including CDS-versus-exon resolution, intron representation, and non-RNA categories. PeakLocus provides a lightweight and interpretable framework for transcript-aware annotation of RNA-associated genomic intervals.
- organism: Drosophila
- organism: mouse
- organism: human
- assay: ChIP-seq
- assay: DNA methylation
- research focus: gene regulatory network inference
- research focus: benchmarking
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- approach: benchmark study
- Citations
- 0
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