SVUPP: Pre-phasing long reads improves structural variant genotyping.

Zilong Li, Frederik Filip Stæger, Robert W Davies, Ida Moltke, Anders Albrechtsen

Abstract read

In one paragraph

Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Flexible read-aware genotype imputation from sequence using biobank sized reference panels.Nature communications · 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

5 authors.

Zilong LiSection for Computational and RNA Biology, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0001-5859-2078

Frederik Filip StægerSection for Computational and RNA Biology, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0002-2295-8637

Robert W DaviesDepartment of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.ORCID 0000-0002-2252-0862

Ida MoltkeSection for Computational and RNA Biology, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0001-7052-8554

Anders AlbrechtsenSection for Computational and RNA Biology, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0001-7306-031X

Funding

Danish Cardiovascular Academy PD2-2025003-DCANovo Nordisk Foundation NNF20OC0061343Villum Young Investigator VIL19114

6 · The paper itself

Abstract

summaryHere, we present an approach, called SVUPP, which improves genotyping of structural variant (SV) by incorporating read phasing information into genotype likelihoods. Through comprehensive benchmarking, we show that SVUPP achieved higher accuracy than cuteSV2, Sniffles2 and kanpig with both long and ultra long Oxford Nanopore Technologies (ONT) data as well as Pacific Biosciences (PacBio) HiFi data for genotyping SVs without close neighbor SVs. SVUPP can be applied together with SV callers such as cuteSV2 and take the per-read phasing information from reference panel based phasing method such as QUILT2 or from reference-free phasing method such as WhatsHap. AVAILABILITY AND IMPLEMENTATION: SVUPP is written in Nextflow with modular design and is freely available here https://github.com/Zilong-Li/SVUPP.

Identifiers

PMID41134129

DOI10.1093/bioinformatics/btaf587

PMCPMC12771361

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LicenceCC BY

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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.