Evidence map›Paper›PMID 34573409›Full record

ArticleGenes2021

CNV Detection from Exome Sequencing Data in Routine Diagnostics of Rare Genetic Disorders: Opportunities and Limitations.

Beryl Royer-Bertrand, Katarina Cisarova, Florence Niel-Butschi, Laureane Mittaz-Crettol, Heidi Fodstad, Andrea Superti-Furga

Abstract read
In one paragraph

Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Whole exome sequencing: a new era in prenatal diagnostics.Journal of translational medicine · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Analytical Validation of a Genomic Newborn Screening Workflow.International journal of neonatal screening · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Observational
  17. Two-Compound Heterozygous Deletions AffectingMolecular syndromology · 2024
    Article
  18. Article
  19. Biallelic Deletion ofMolecular syndromology · 2024
    Article
  20. 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.

Beryl Royer-BertrandDivision of Genetic Medicine, Lausanne University Hospital (CHUV), University of Lausanne, 1011 Lausanne, Switzerland.
Katarina CisarovaDivision of Genetic Medicine, Lausanne University Hospital (CHUV), University of Lausanne, 1011 Lausanne, Switzerland.ORCID 0000-0003-2711-0480
Florence Niel-ButschiDivision of Genetic Medicine, Lausanne University Hospital (CHUV), University of Lausanne, 1011 Lausanne, Switzerland.
Laureane Mittaz-CrettolDivision of Genetic Medicine, Lausanne University Hospital (CHUV), University of Lausanne, 1011 Lausanne, Switzerland.
Heidi FodstadDivision of Genetic Medicine, Lausanne University Hospital (CHUV), University of Lausanne, 1011 Lausanne, Switzerland.
Andrea Superti-FurgaDivision of Genetic Medicine, Lausanne University Hospital (CHUV), University of Lausanne, 1011 Lausanne, Switzerland.ORCID 0000-0002-3543-7531

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To assess the potential of detecting copy number variations (CNVs) directly from exome sequencing (ES) data in diagnostic settings, we developed a CNV-detection pipeline based on ExomeDepth software and applied it to ES data of 450 individuals. Initially, only CNVs affecting genes in the requested diagnostic gene panels were scored and tested against arrayCGH results. Pathogenic CNVs were detected in 18 individuals. Most detected CNVs were larger than 400 kb (11/18), but three individuals had small CNVs impacting one or a few exons only and were thus not detectable by arrayCGH. Conversely, two pathogenic CNVs were initially missed, as they impacted genes not included in the original gene panel analysed, and a third one was missed as it was in a poorly covered region. The overall combined diagnostic rate (SNVs + CNVs) in our cohort was 36%, with wide differences between clinical domains. We conclude that (1) the ES-based CNV pipeline detects efficiently large and small pathogenic CNVs, (2) the detection of CNV relies on uniformity of sequencing and good coverage, and (3) in patients who remain unsolved by the gene panel analysis, CNV analysis should be extended to all captured genes, as diagnostically relevant CNVs may occur everywhere in the genome.

Indexed as

DNA Copy Number VariationsAdolescentAdultAgedAged, 80 and overChildChild, PreschoolCohort StudiesDiagnostic Tests, RoutineExome SequencingFemaleGenetic TestingHigh-Throughput Nucleotide SequencingHumansInfantMalearrayCGH (aCGH)copy number variations (CNVs)exome sequencing (ES)MLPAnext-generation sequencing (NGS)rare and undiagnosed diseasestructural variation (SV)

Identifiers

PMID34573409
PMCPMC8472439

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.