Evidence map›Paper›PMID 40575478›Full record

ArticleBioinformatics advances2025

Harpy: a pipeline for processing haplotagging linked-read data.

Pavel V Dimens, Ryan P Franckowiak, Azwad Iqbal, Jennifer K Grenier, Paul R Munn, Nina Overgaard Therkildsen

Abstract read
In one paragraph

Article in Bioinformatics advances, 2025. 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

6 authors.

Pavel V DimensDepartment of Natural Resources and the Environment, Cornell University, Ithaca, NY 14853, United States.ORCID https://orcid.org/0000-0003-3823-0373
Ryan P FranckowiakDepartment of Natural Resources and the Environment, Cornell University, Ithaca, NY 14853, United States.ORCID https://orcid.org/0000-0002-0454-4860
Azwad IqbalDepartment of Natural Resources and the Environment, Cornell University, Ithaca, NY 14853, United States.ORCID https://orcid.org/0000-0002-8266-7284
Jennifer K GrenierGenomics Innovation Hub, Biotechnology Resource Center, Cornell University, Ithaca, NY 14853, United States.ORCID https://orcid.org/0000-0002-0928-7971
Paul R MunnGenomics Innovation Hub, Biotechnology Resource Center, Cornell University, Ithaca, NY 14853, United States.ORCID https://orcid.org/0000-0001-9316-0879
Nina Overgaard TherkildsenDepartment of Natural Resources and the Environment, Cornell University, Ithaca, NY 14853, United States.ORCID https://orcid.org/0000-0002-6591-591X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Haplotagging is a method for linked-read sequencing, which leverages the cost-effectiveness and throughput of short-read sequencing while retaining part of the long-range haplotype information captured by long-read sequencing. Despite its utility and advantages over similar methods, existing linked-read analytical pipelines are incompatible with haplotagging data. Results: We describe Harpy, a modular and user-friendly software pipeline for processing all stages of haplotagged linked-read data, from raw sequence data to phased genotypes and structural variant detection. Availability and implementation: https://github.com/pdimens/harpy.

Identifiers

PMID40575478
PMCPMC12198493

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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.