Evidence map›Paper›PMID 21325948›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2011

Global analysis of disease-related DNA sequence variation in 10 healthy individuals: implications for whole genome-based clinical diagnostics.

Barry Moore, Hao Hu, Marc Singleton, Francisco M De La Vega, Martin G Reese, Mark Yandell

Open access · bronzeAbstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.8field-weighted citation impact, top 4% of its field
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

19 citing papers in PubMed, 37 citations in OpenAlex.

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  14. Taxonomizing, sizing, and overcoming the incidentalome.Genetics in medicine : official journal of the American College of Medical Genetics · 2012
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  19. Utility of gene-specific algorithms for predicting pathogenicity of uncertain gene variants.Journal of the American Medical Informatics Association : JAMIA
    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

6 authors at 3 institutions in 3 countries.

Barry MooreDepartment of Human Genetics, Eccles Institute of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, USA.
Hao Hu
Marc Singleton
Francisco M De La Vega
Martin G Reese
Mark Yandell
University of Utah · USLife Systems (United States) · USOmicia (United States) · US

Funding

Clinical Genome Inference System: Variant Prioritization for Clinical DiagnosticsR44HG006579 · NHGRI · FABRIC GENOMICS INC. · PI REESE, MARTIN G, YANDELL, MARK DOUGLAS · 2012 to 2013
$1.8M
System for genetic marker information deliveryR44HG002991 · NHGRI · FABRIC GENOMICS INC. · PI REESE, MARTIN G · 2008 to 2010
$1.0M
Disease marker genome annotation systemR44HG002993 · NHGRI · OMICIA, INC. · PI REESE, MARTIN G · 2005 to 2007
$1000k
Computational system to predict novel genetic disease associationsR44HG003667 · NHGRI · FABRIC GENOMICS INC. · PI REESE, MARTIN G, YANDELL, MARK DOUGLAS · 2009 to 2010
$851k
Tool for annotation and analyses of human whole-genome sequence variation dataRC2HG005619 · NHGRI · UNIVERSITY OF UTAH · PI REESE, MARTIN G, YANDELL, MARK DOUGLAS · 2009 to 2010
$785k
System to predict novel genetic disease associationsR43HG003667 · NHGRI · OMICIA, INC. · PI REESE, MARTIN G · 2005 to 2005
$100k
NHGRI NIH HHS 1R4HG003667NHGRI NIH HHS 1RC2HG005619-01NHGRI NIH HHS R43 HG003667NHGRI NIH HHS R44 HG002991NHGRI NIH HHS R44 HG002993NHGRI NIH HHS R44 HG003667NHGRI NIH HHS R44 HG006579NHGRI NIH HHS RC2 HG005619
6 · The paper itself

Abstract

backgroundUnderstanding how sequence variants within healthy genomes are distributed with respect to ethnicity and disease-implicated genes is an essential first step toward establishing baselines for personalized genomic medicine.

methodsIn this study, we present an analysis of 10 genomes from healthy individuals of various ethnicities, produced using six different sequencing technologies. In total, these genomes contain more than 34 million single-nucleotide variants.

resultsWe have analyzed these variants from a clinical perspective, assaying the influence of sequencing technology and ethnicity on prognosis. We have also examined the utility of OMIM and the disease-gene literature for determining the impact of rare, personal variants on an individual's health.

conclusionsOur analyses demonstrate that clinical prognoses are complicated by sequencing platform-specific errors and ethnicity. We show that disease-causing alleles are globally distributed along ethnic lines, with alleles known to be disease causing in Eurasians being significantly more likely to be homozygous in Africans.

Indexed as

Genetics, MedicalGenomePrecision MedicineAllelesComputational BiologyDatabases, GeneticFemaleGenome-Wide Association StudyHumansMaleMolecular Sequence AnnotationMutationPolymorphism, Single NucleotideRacial GroupsSequence Analysis, DNA

Identifiers

PMID21325948
PMCPMC3558030
OpenAlexW2112228737

What OpenQuestion holds

Textmetadata
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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.