Evidence map›Paper›PMID 36658279›Full record

ArticleNature methods2023

Jasmine and Iris: population-scale structural variant comparison and analysis.

Melanie Kirsche, Gautam Prabhu, Rachel Sherman, Bohan Ni, Alexis Battle, Sergey Aganezov, Michael C Schatz

Abstract read
In one paragraph

Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers.

0numbers the graph read from it
0cells of the map it votes in
103citing 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

103 citing papers in PubMed.

  1. Article
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  5. Article
  6. Article
  7. Review
  8. Population-scale detection of methylation outliers from long-read genome sequencing.medRxiv : the preprint server for health sciences · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. cuteHap: Haplotype-Aware Structural Variant Detection in Phased Long-Read Sequencing Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  19. Article
  20. Article

43 more citing papers are in PubMed but not listed here.

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

7 authors.

Melanie KirscheDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-6631-4761
Gautam PrabhuDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0000-0003-3105-993X
Rachel ShermanDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0000-0003-1750-8428
Bohan NiDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Alexis BattleDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-5287-627X
Sergey AganezovDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA. sergeyaganezovjr@gmail.com.ORCID http://orcid.org/0000-0003-2458-8323
Michael C SchatzDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA. mschatz@cs.jhu.edu.ORCID http://orcid.org/0000-0002-4118-4446

Funding

Implementing the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)U24HG010263 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI Enis Afgan, VINCENT JAMES CAREY · 2018 to 2026
$23.8M
Democratization of Data Analysis in Life Sciences Through GalaxyU41HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI NEKRUTENKO, ANTON, SCHATZ, MICHAEL · 2012 to 2020
$14.4M
Democratization of Data Analysis in Life Sciences Through GalaxyU24HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI Daniel James Blankenberg, Jeremy Goecks · 2021 to 2026
$9.8M
A Federated Galaxy for user-friendly large-scale cancer genomics researchU24CA231877 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI GOECKS, JEREMY · 2018 to 2022
$3.9M
Modeling the dynamicimpact of rare and common genetic variation on gene expression anddiseaseR35GM139580 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BATTLE, ALEXIS · 2021 to 2025
$3.1M
Integrative genomic and epigenomic analysis of cancer using long read sequencingU01CA253481 · NCI · JOHNS HOPKINS UNIVERSITY · PI SCHATZ, MICHAEL · 2021 to 2023
$1.1M
Optimized workflows for structural variant analysis of the Kids First genomes using short and long readsR03CA272952 · NCI · JOHNS HOPKINS UNIVERSITY · PI SCHATZ, MICHAEL · 2022 to 2023
$312k
NCI NIH HHS R03 CA272952NCI NIH HHS U01 CA253481NCI NIH HHS U24 CA231877NHGRI NIH HHS U24 HG006620NHGRI NIH HHS U24 HG010263NHGRI NIH HHS U41 HG006620NIGMS NIH HHS R35 GM139580
6 · The paper itself

Abstract

The availability of long reads is revolutionizing studies of structural variants (SVs). However, because SVs vary across individuals and are discovered through imprecise read technologies and methods, they can be difficult to compare. Addressing this, we present Jasmine and Iris ( https://github.com/mkirsche/Jasmine/ ), for fast and accurate SV refinement, comparison and population analysis. Using an SV proximity graph, Jasmine outperforms six widely used comparison methods, including reducing the rate of Mendelian discordance in trio datasets by more than fivefold, and reveals a set of high-confidence de novo SVs confirmed by multiple technologies. We also present a unified callset of 122,813 SVs and 82,379 indels from 31 samples of diverse ancestry sequenced with long reads. We genotype these variants in 1,317 samples from the 1000 Genomes Project and the Genotype-Tissue Expression project with DNA and RNA-sequencing data and assess their widespread impact on gene expression, including within medically relevant genes.

Indexed as

JasminumGenomeGenome, HumanGenotypeHigh-Throughput Nucleotide SequencingHumansIrisSequence AnalysisSequence Analysis, DNASoftware

Identifiers

PMID36658279
PMCPMC10006329

What OpenQuestion holds

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Read underepoch 390

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.