Evidence map›Paper›PMID 28804138›Full record

ReviewNature reviews. Genetics2017

Settling the score: variant prioritization and Mendelian disease.

Karen Eilbeck, Aaron Quinlan, Mark Yandell

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 138 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
138citing papers in PubMed, 1 pooled it
–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

138 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
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  6. Review
  7. Article
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  12. Genetics of Congenital Heart Disease.Clinics in perinatology · 2025
    Review
  13. Article
  14. Advances in laboratory medicine · 2025
    Article
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  17. Article
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  19. Review
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78 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.

Karen EilbeckDepartment of Biomedical Informatics, School of Medicine, University of Utah, 421 Wakara Way, Suite 120, Salt Lake City, Utah 84108, USA.
Aaron QuinlanDepartment of Biomedical Informatics, School of Medicine, University of Utah, 421 Wakara Way, Suite 120, Salt Lake City, Utah 84108, USA.
Mark YandellDepartment of Human Genetics, Eccles Institute of Human Genetics, School of Medicine, University of Utah, 15 S 2030 E, Salt Lake City, Utah 84112, USA.

Funding

Resource ProjectU41HG006834 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI MARTIN, CHRISTA LESE, REHM, HEIDI L · 2013 to 2020
$26.9M
University of Utah Center for Clinical and Translational ScienceUL1TR001067 · NCATS · UNIVERSITY OF UTAH · PI DERE, WILLARD H., HESS, RACHEL · 2013 to 2017
$19.8M
A Knowledge Base for Clinically Relevant Genes and VariantsU01HG007437 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERG, JONATHAN S, EVANS, JAMES PHILIP · 2013 to 2016
$9.0M
Monitoring tumor subclonal heterogeneity over time and spaceU24CA209999 · NCI · UNIVERSITY OF UTAH · PI MARTH, GABOR T, QUINLAN, AARON R · 2016 to 2020
$3.9M
Integrating Genomic and Clinical Approaches to Sudden Death in the YoungU01HL131698 · NHLBI · UNIVERSITY OF UTAH · PI TRISTANI-FIROUZI, MARTIN, YANDELL, MARK DOUGLAS · 2016 to 2019
$3.2M
New algorithms and tools for large-scale genomic analysesR01HG006693 · NHGRI · UNIVERSITY OF VIRGINIA · PI QUINLAN, AARON R · 2012 to 2018
$3.1M
VAAST+: Tool for variant prioritization, risk assessment and disease-gene findingR01GM104390 · NIGMS · UNIVERSITY OF UTAH · PI JORDE, LYNN, YANDELL, MARK DOUGLAS · 2013 to 2017
$2.2M
Bridging the Gap between Genomics and Clinical Outcomes in CHDUM1HL128711 · NHLBI · UNIVERSITY OF UTAH · PI TRISTANI-FIROUZI, MARTIN, YANDELL, MARK DOUGLAS · 2015 to 2019
$2.0M
A Community Driven Framework for Genome Based Clinical DiagnosticsR01HG008628 · NHGRI · UNIVERSITY OF UTAH · PI EILBECK, KAREN LOUISE, MARTH, GABOR T · 2015 to 2017
$1.8M
NCATS NIH HHS UL1 TR001067NCI NIH HHS U24 CA209999NHGRI NIH HHS R01 HG006693NHGRI NIH HHS R01 HG008628NHGRI NIH HHS U01 HG007437NHGRI NIH HHS U41 HG006834NHLBI NIH HHS U01 HL131698NHLBI NIH HHS UM1 HL128711NIGMS NIH HHS R01 GM104390
6 · The paper itself

Abstract

When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype-phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

Indexed as

Genetic VariationDiseaseDNA Copy Number VariationsGenetic StructuresGenome, HumanGenome-Wide Association StudyHumans

Identifiers

PMID28804138
PMCPMC5935497

What OpenQuestion holds

Textmetadata
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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.