Evidence map›Paper›PMID 25356966›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2015

Assessing copy number from exome sequencing and exome array CGH based on CNV spectrum in a large clinical cohort.

Kyle Retterer, Julie Scuffins, Daniel Schmidt, Rachel Lewis, Daniel Pineda-Alvarez, Amanda Stafford, Lindsay Schmidt, Stephanie Warren, Federica Gibellini, Anastasia Kondakova and 6 more

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In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing 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

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

  1. Pooled it
  2. Trial
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  6. Integrating Long-Read Nanopore Sequencing for Precision Resolution of Genomic Variants in Dystonia.Movement disorders : official journal of the Movement Disorder Society · 2026
    Article
  7. Co-morbid monogenic disorders at chromosome region 1q2: LMNA- and FLG-related disorders in a patient referred for assessment of joint hypermobility.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2025
    Article
  8. Article
  9. Monogenic disorders associated with motor speech phenotypes in children and adolescents undergoing clinical exome sequencing.Genetics in medicine : official journal of the American College of Medical Genetics · 2025
    Article
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13 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

16 authors.

Kyle RettererGeneDx, Gaithersburg, Maryland, USA.ORCID 0000000152522001
Julie ScuffinsGeneDx, Gaithersburg, Maryland, USA.
Daniel SchmidtGeneDx, Gaithersburg, Maryland, USA.
Rachel LewisGeneDx, Gaithersburg, Maryland, USA.
Daniel Pineda-AlvarezGeneDx, Gaithersburg, Maryland, USA.
Amanda StaffordGeneDx, Gaithersburg, Maryland, USA.
Lindsay SchmidtGeneDx, Gaithersburg, Maryland, USA.
Stephanie WarrenGeneDx, Gaithersburg, Maryland, USA.
Federica GibelliniGeneDx, Gaithersburg, Maryland, USA.
Anastasia KondakovaGeneDx, Gaithersburg, Maryland, USA.
Amanda BlairGeneDx, Gaithersburg, Maryland, USA.
Sherri BaleGeneDx, Gaithersburg, Maryland, USA.
Ludmila MatyakhinaGeneDx, Gaithersburg, Maryland, USA.
Jeanne MeckGeneDx, Gaithersburg, Maryland, USA.
Swaroop AradhyaGeneDx, Gaithersburg, Maryland, USA.
Eden HaverfieldGeneDx, Gaithersburg, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDetection of copy-number variation (CNV) is important for investigating many genetic disorders. Testing a large clinical cohort by array comparative genomic hybridization provides a deep perspective on the spectrum of pathogenic CNV. In this context, we describe a bioinformatics approach to extract CNV information from whole-exome sequencing and demonstrate its utility in clinical testing.

methodsExon-focused arrays and whole-genome chromosomal microarray analysis were used to test 14,228 and 14,000 individuals, respectively. Based on these results, we developed an algorithm to detect deletions/duplications in whole-exome sequencing data and a novel whole-exome array.

resultsIn the exon array cohort, we observed a positive detection rate of 2.4% (25 duplications, 318 deletions), of which 39% involved one or two exons. Chromosomal microarray analysis identified 3,345 CNVs affecting single genes (18%). We demonstrate that our whole-exome sequencing algorithm resolves CNVs of three or more exons.

conclusionThese results demonstrate the clinical utility of single-exon resolution in CNV assays. Our whole-exome sequencing algorithm approaches this resolution but is complemented by a whole-exome array to unambiguously identify intragenic CNVs and single-exon changes. These data illustrate the next advancements in CNV analysis through whole-exome sequencing and whole-exome array.Genet Med 17 8, 623-629.

Indexed as

DNA Copy Number VariationsExomeAlgorithmsCohort StudiesComparative Genomic HybridizationComputational BiologyDNAGenetic VariationHigh-Throughput Nucleotide SequencingHumansDNA

Identifiers

PMID25356966

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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.