Evidence map›Paper›PMID 42779890›Full record

ArticlebioRxiv : the preprint server for biology2026

Bramble: projection of spliced genomic alignments into transcriptomic space for improved transcript quantification.

Zoe Rudnick, Ales Varabyou, Rob Patro, Mihaela Pertea

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zoe RudnickJohns Hopkins University, Center for Computational Biology, Baltimore, MD.ORCID 0009-0004-4883-2305
Ales VarabyouJohns Hopkins University, Center for Computational Biology, Baltimore, MD.
Rob PatroUniversity of Maryland Institute for Advanced Computer Studies, Center for Bioinformatics and Computational Biology, College Park, MD.
Mihaela PerteaJohns Hopkins University, Center for Computational Biology, Baltimore, MD.

Funding

A Modular Framework for Accurate, Interpretable, and Reproducible Analysis of Long Read RNA-Seq DataR01HG009937 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Michael Isaiah Love, Robert Patro · 2018 to 2026
$2.8M
Exploring new approaches for enhanced human gene annotationR35GM156470 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Mihaela Pertea · 2025 to 2026
$776k
NHGRI NIH HHS R01 HG009937NIGMS NIH HHS R35 GM156470
6 · The paper itself

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.

Identifiers

PMID42779890
PMCPMC13596574

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.