Evidence map›Paper›PMID 26147798›Full record

ArticlePloS one2015

The Use of Non-Variant Sites to Improve the Clinical Assessment of Whole-Genome Sequence Data.

Alberto Ferrarini, Luciano Xumerle, Francesca Griggio, Marianna Garonzi, Chiara Cantaloni, Cesare Centomo, Sergio Marin Vargas, Patrick Descombes, Julien Marquis, Sebastiano Collino and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.5field-weighted citation impact, top 26% 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

11 citing papers in PubMed, 22 citations in OpenAlex.

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  10. Catching hidden variation: systematic correction of reference minor allele annotation in clinical variant calling.Genetics in medicine : official journal of the American College of Medical Genetics · 2018
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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

15 authors at 4 institutions in 2 countries.

Alberto FerrariniFunctional Genomics Center, Department of Biotechnology, University of Verona, 37134, Verona, Italy.
Luciano XumerlePersonal Genomics s.r.l, Strada le Grazie 15, 37134, Verona, Italy.
Francesca GriggioFunctional Genomics Center, Department of Biotechnology, University of Verona, 37134, Verona, Italy; Personal Genomics s.r.l, Strada le Grazie 15, 37134, Verona, Italy.
Marianna GaronziFunctional Genomics Center, Department of Biotechnology, University of Verona, 37134, Verona, Italy.
Chiara CantaloniFunctional Genomics Center, Department of Biotechnology, University of Verona, 37134, Verona, Italy; Personal Genomics s.r.l, Strada le Grazie 15, 37134, Verona, Italy.
Cesare CentomoFunctional Genomics Center, Department of Biotechnology, University of Verona, 37134, Verona, Italy.
Sergio Marin VargasFunctional Genomics Center, Department of Biotechnology, University of Verona, 37134, Verona, Italy.
Patrick DescombesFunctional Genomics, Nestlé Institute of Health Sciences SA, EPFL Innovation Park, bâtiment G, 1015, Lausanne, Switzerland.
Julien MarquisFunctional Genomics, Nestlé Institute of Health Sciences SA, EPFL Innovation Park, bâtiment G, 1015, Lausanne, Switzerland.
Sebastiano CollinoMolecular Biomarkers, Nestlé Institute of Health Sciences SA, EPFL Innovation Park, bâtiment H, 1015, Lausanne, Switzerland.
Claudio FranceschiPersonal Genomics s.r.l, Strada le Grazie 15, 37134, Verona, Italy; Department of Experimental, Diagnostic and Specialty Medicine Experimental Pathology, University of Bologna, Via S. Giacomo 12, 40126, Bologna, Italy; Interdepartmental Centre "L. Galvani" (CIG), University of Bologna, Piazza di Porta S. Donato 1, 40126, Bologna, Italy; IRCCS, Institute of Neurological Sciences of Bologna, Ospedale Bellaria, Via Altura 3, 40139, Bologna, Italy.
Paolo GaragnaniPersonal Genomics s.r.l, Strada le Grazie 15, 37134, Verona, Italy; Department of Experimental, Diagnostic and Specialty Medicine Experimental Pathology, University of Bologna, Via S. Giacomo 12, 40126, Bologna, Italy; Interdepartmental Centre "L. Galvani" (CIG), University of Bologna, Piazza di Porta S. Donato 1, 40126, Bologna, Italy; Center for Applied Biomedical Research, St. Orsola-Malpighi University Hospital, 40138, Bologna, Italy.
Benjamin A SalisburyKnome Inc., Waltham, Massachusetts, 02451, United States of America.
John Max HarveyKnome Inc., Waltham, Massachusetts, 02451, United States of America.
Massimo DelledonneFunctional Genomics Center, Department of Biotechnology, University of Verona, 37134, Verona, Italy; Personal Genomics s.r.l, Strada le Grazie 15, 37134, Verona, Italy.
University of Verona · ITÉcole Polytechnique Fédérale de Lausanne · CHUniversity of Bologna · ITNestlé (Switzerland) · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic testing, which is now a routine part of clinical practice and disease management protocols, is often based on the assessment of small panels of variants or genes. On the other hand, continuous improvements in the speed and per-base costs of sequencing have now made whole exome sequencing (WES) and whole genome sequencing (WGS) viable strategies for targeted or complete genetic analysis, respectively. Standard WGS/WES data analytical workflows generally rely on calling of sequence variants respect to the reference genome sequence. However, the reference genome sequence contains a large number of sites represented by rare alleles, by known pathogenic alleles and by alleles strongly associated to disease by GWAS. It's thus critical, for clinical applications of WGS and WES, to interpret whether non-variant sites are homozygous for the reference allele or if the corresponding genotype cannot be reliably called. Here we show that an alternative analytical approach based on the analysis of both variant and non-variant sites from WGS data allows to genotype more than 92% of sites corresponding to known SNPs compared to 6% genotyped by standard variant analysis. These include homozygous reference sites of clinical interest, thus leading to a broad and comprehensive characterization of variation necessary to an accurate evaluation of disease risk. Altogether, our findings indicate that characterization of both variant and non-variant clinically informative sites in the genome is necessary to allow an accurate clinical assessment of a personal genome. Finally, we propose a highly efficient extended VCF (eVCF) file format which allows to store genotype calls for sites of clinical interest while remaining compatible with current variant interpretation software.

Indexed as

AllelesGenome, HumanGenome-Wide Association StudyHomozygotePolymorphism, Single NucleotideExomeFemaleHigh-Throughput Nucleotide SequencingHumansLong QT SyndromeMale

Identifiers

PMID26147798
PMCPMC4492948
OpenAlexW2154238026

What OpenQuestion holds

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LicenceCC BY
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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.