Bramble: projection of spliced genomic alignments into transcriptomic space for improved transcript quantification
- 1Johns Hopkins University
Abstract
Accurate transcript abundance estimation is central to many transcriptomic studies. Many current quantification methods rely on reads mapped directly to the transcriptome, but transcriptome alignment can misassign reads from unannotated transcripts to annotated isoforms, leading to biased abundance estimates. We introduce Bramble, a method that projects spliced genomic alignments into transcriptomic coordinates to produce alignments compatible with downstream transcript quantification tools. Across simulated short- and long-read RNA-seq datasets and multiple levels of reference annotation completeness, incorporating Bramble into quantification pipelines consistently improved accuracy and reduced error. These results suggest that genome-derived transcriptomic alignments can improve transcript quantification by preserving compatible alignments to annotated transcripts while filtering alignments likely originating from unannotated transcripts.
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BibTeX
@misc{rudnick2026bramble,
title = {{Bramble: projection of spliced genomic alignments into transcriptomic space for improved transcript quantification}},
author = {Z. Rudnick and A. Varabyou and R. Patro and M. Pertea},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.09.750464},
url = {https://www.biorxiv.org/content/10.64898/2026.09.09.750464v1},
note = {CC BY-ND},
}
RIS
TY - UNPB
TI - Bramble: projection of spliced genomic alignments into transcriptomic space for improved transcript quantification
AU - Z. Rudnick
AU - A. Varabyou
AU - R. Patro
AU - M. Pertea
PY - 2026
DA - 2026/09/09
PB - bioRxiv
DO - 10.64898/2026.09.09.750464
UR - https://www.biorxiv.org/content/10.64898/2026.09.09.750464v1
AB - Accurate transcript abundance estimation is central to many transcriptomic studies. Many current quantification methods rely on reads mapped directly to the transcriptome, but transcriptome alignment can misassign reads from unannotated transcripts to annotated isoforms, leading to biased abundance estimates. We introduce Bramble, a method that projects spliced genomic alignments into transcriptomic coordinates to produce alignments compatible with downstream transcript quantification tools. Across simulated short- and long-read RNA-seq datasets and multiple levels of reference annotation completeness, incorporating Bramble into quantification pipelines consistently improved accuracy and reduced error. These results suggest that genome-derived transcriptomic alignments can improve transcript quantification by preserving compatible alignments to annotated transcripts while filtering alignments likely originating from unannotated transcripts.
ER -