Evidence map›Paper›PMID 41912802›Full record

ArticleNature methods2026

SNP calling, haplotype phasing and allele-specific analysis with long RNA-seq reads.

Neng Huang, Heng Li, Human Pangenome Reference Consortium

Abstract read
In one paragraph

Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. AlleleMiner: a long-read pipeline for gene-wise de novo allele phasing and variant detection in diploid citrus cultivars.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026
    Article
  2. Article
  3. Article
  4. Accelerated Tempo of Cortical Neurogenesis in Down Syndrome.bioRxiv : the preprint server for biology · 2025
    Article
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

3 authors.

Neng HuangDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.ORCID http://orcid.org/0000-0001-7187-0749
Heng LiDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA. hli@ds.dfci.harvard.edu.ORCID http://orcid.org/0000-0003-4874-2874
Human Pangenome Reference Consortium

Funding

The WashU-UCSC-EBI Human Genome Reference Center."U41HG010972 · NHGRI · WASHINGTON UNIVERSITY · PI Ira M Hall, Heng Li · 2019 to 2026
$24.9M
ELSI Administrative Supplement - Center for Human Reference Genome DiversityU01HG010971 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI EICHLER, EVAN, JARVIS, ERICH D · 2019 to 2023
$18.4M
Telomere-to-telomere assemblies of human genomesR01HG011274 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI Karen Hayden Miga · 2020 to 2026
$4.5M
Advanced computational methods in analyzing high-throughput sequencing dataR01HG010040 · NHGRI · DANA-FARBER CANCER INST · PI Heng Li · 2018 to 2026
$3.7M
Enhancement and further development of informatics methods for long-read cancer sequencingU24CA294203 · NCI · DANA-FARBER CANCER INST · PI Catarina D. Campbell, Heng Li · 2024 to 2026
$2.6M
Tools for comprehensive variant characterization using the pangenomeU01HG013748 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI LI, HENG, MARSCHALL, TOBIAS · 2024 to 2024
$1.7M
Building Tools and Community to Make Pangenomes AccessibleU01HG013760 · NHGRI · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI GARRISON, ERIK · 2024 to 2024
$1.6M
Tooling for accurately studying the epigenome along the human pangenome referenceU01HG013744 · NHGRI · UNIVERSITY OF WASHINGTON · PI STERGACHIS, ANDREW BEN · 2024 to 2024
$1.4M
Integrating the reference pangenome with biobank-scale data for complex trait analysisU01HG013755 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GYMREK, MELISSA · 2024 to 2024
$1.3M
Calling germline and mosaic variants from long genomic and RNA-seq readsR01HG014175 · NHGRI · DANA-FARBER CANCER INST · PI Heng Li · 2025 to 2026
$1.0M
NCI NIH HHS U24 CA294203NHGRI NIH HHS R01 HG010040NHGRI NIH HHS R01 HG014175NHGRI NIH HHS U01 HG013748NHGRI NIH HHS U41 HG010972U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) R01HG010040U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) R01HG011274U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) R01HG014175U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U01HG010971U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U01HG013744U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U01HG013748U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U01HG013755U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U01HG013760U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U24CA294203U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U41HG010972
6 · The paper itself

Abstract

Long-read RNA sequencing is a powerful technology to link transcript structures to genetic variants, but this type of analysis is not often performed owing to the lack of end-user tools. Here we introduce longcallR for joint single-nucleotide polymorphism calling, haplotype phasing and allele-specific analysis, which achieves high accuracy on benchmark datasets. Applied to 202 human samples, longcallR identified 88 significant allele-specific splicing events per sample on average, of which 46% involved unannotated junctions.

Identifiers

PMID41912802
PMCPMC13041723

What OpenQuestion holds

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Registered trials

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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.