Evidence map›Paper›PMID 31729472›Full record

ReviewNature reviews. Genetics2020

Structural variation in the sequencing era.

Steve S Ho, Alexander E Urban, Ryan E Mills

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 350 papers.

0numbers the graph read from it
0cells of the map it votes in
350citing 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

350 citing papers in PubMed.

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  15. DNA Replication Errors Drive Genome-Wide Small Inverted Triplication Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  16. Article
  17. Detection of a complex chromosomal rearrangement in a novel mouse mutant by optical genome mapping.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  18. Article
  19. Article
  20. Article

290 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

3 authors.

Steve S HoDepartment of Human Genetics, University of Michigan, Ann Arbor, MI, USA.ORCID http://orcid.org/0000-0002-6685-774X
Alexander E UrbanDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Ryan E MillsDepartment of Human Genetics, University of Michigan, Ann Arbor, MI, USA. remills@umich.edu.ORCID http://orcid.org/0000-0003-3425-6998

Funding

PREDOCTORAL TRAINING IN GENETICST32GM007544 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MORAN, JOHN V. · 1985 to 2022
$11.3M
NIGMS NIH HHS T32 GM007544
6 · The paper itself

Abstract

Identifying structural variation (SV) is essential for genome interpretation but has been historically difficult due to limitations inherent to available genome technologies. Detection methods that use ensemble algorithms and emerging sequencing technologies have enabled the discovery of thousands of SVs, uncovering information about their ubiquity, relationship to disease and possible effects on biological mechanisms. Given the variability in SV type and size, along with unique detection biases of emerging genomic platforms, multiplatform discovery is necessary to resolve the full spectrum of variation. Here, we review modern approaches for investigating SVs and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.

Indexed as

Genomic Structural VariationAlgorithmsGenome, HumanHumansSequence Analysis

Identifiers

PMID31729472
PMCPMC7402362

What OpenQuestion holds

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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.