Evidence map›Paper›PMID 23897863›Full record

ArticleAmerican journal of medical genetics. Part A2013

PECONPI: a novel software for uncovering pathogenic copy number variations in non-syndromic sensorineural hearing loss and other genetically heterogeneous disorders.

Ellen A Tsai, Micah A Berman, Laura K Conlin, Heidi L Rehm, Lauren J Francey, Matthew A Deardorff, Jenelle Holst, Maninder Kaur, Emily Gallant, Dinah M Clark and 7 more

Abstract read
In one paragraph

Article in American journal of medical genetics. Part A, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Cardiovascular Nursing in Rehabilitative Cardiology: A Review.Journal of cardiovascular development and disease · 2025
    Review
  3. Article
  4. Article
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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

17 authors at 4 institutions in 1 country.

Ellen A TsaiGenomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Micah A Berman
Laura K Conlin
Heidi L Rehm
Lauren J Francey
Matthew A Deardorff
Jenelle Holst
Maninder Kaur
Emily Gallant
Dinah M Clark
Joseph T Glessner
Shane T Jensen
Struan F A Grant
Peter J Gruber
Hakon Hakonarson
Nancy B Spinner
Ian D Krantz
Children's Hospital of Philadelphia · USUniversity of Pennsylvania · USMass General Brigham · USPrimary Children's Hospital · US

Funding

Applying Genomic Sequencing in PediatricsU01HG006546 · NHGRI · CHILDREN'S HOSP OF PHILADELPHIA · PI KRANTZ, IAN D. · 2012 to 2016
$10.6M
Training Program in Computational GenomicsT32HG000046 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI JUNHYONG KIM, Mingyao Li · 1999 to 2026
$9.5M
MEDICAL GENETICS RESEARCH TRAINING GRANTT32GM008638 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Rebecca Ganetzky · 1997 to 2026
$8.7M
Audiological and Genetic Resource for Pediatric Hearing ResearchR24DC012207 · NIDCD · CHILDREN'S HOSP OF PHILADELPHIA · PI CRENSHAW, E BRYAN · 2012 to 2016
$3.9M
Audiological and Genetic Resource for Pediatric Hearing ResearchR33DC008630 · NIDCD · CHILDREN'S HOSP OF PHILADELPHIA · PI CRENSHAW, E BRYAN · 2009 to 2011
$2.1M
Outcomes of Genetic Testing for Hearing ImpairmentR01DC005247 · NIDCD · CHILDRENS HOSPITAL OF PHILADELPHIA · PI KRANTZ, IAN D · 2002 to 2005
$1.7M
Training in the Neurobiology of OtorhinolaryngologyT32DC005363 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI SAUNDERS, JAMES C · 2003 to 2007
$1.5M
NHGRI NIH HHS T32 HG000046NHGRI NIH HHS T32HG000046NHGRI NIH HHS U01 HG006546NHGRI NIH HHS U01HG006546NIDCD NIH HHS R01 DC005247NIDCD NIH HHS R01DC005247NIDCD NIH HHS R24 DC012207NIDCD NIH HHS R33 DC008630NIDCD NIH HHS R33DC008630NIDCD NIH HHS T32 DC005363NIDCD NIH HHS T32DC005363NIGMS NIH HHS T32 GM008638NIGMS NIH HHS T32GM008638
6 · The paper itself

Abstract

This report describes an algorithm developed to predict the pathogenicity of copy number variants (CNVs) in large sample cohorts. CNVs (genomic deletions and duplications) are found in healthy individuals and in individuals with genetic diagnoses, and differentiation of these two classes of CNVs can be challenging and usually requires extensive manual curation. We have developed PECONPI, an algorithm to assess the pathogenicity of CNVs based on gene content and CNV frequency. This software was applied to a large cohort of patients with genetically heterogeneous non-syndromic hearing loss to score and rank each CNV based on its relative pathogenicity. Of 636 individuals tested, we identified the likely underlying etiology of the hearing loss in 14 (2%) of the patients (1 with a homozygous deletion, 7 with a deletion of a known hearing loss gene and a point mutation on the trans allele and 6 with a deletion larger than 1 Mb). We also identified two probands with smaller deletions encompassing genes that may be functionally related to their hearing loss. The ability of PECONPI to determine the pathogenicity of CNVs was tested on a second genetically heterogeneous cohort with congenital heart defects (CHDs). It successfully identified a likely etiology in 6 of 355 individuals (2%). We believe this tool is useful for researchers with large genetically heterogeneous cohorts to help identify known pathogenic causes and novel disease genes.

Indexed as

SoftwareDNA Copy Number VariationsExtracellular Matrix ProteinsGene DeletionGenomicsGenotypeHearing Loss, SensorineuralHeart Defects, CongenitalHumansIn Situ Hybridization, FluorescencePolymorphism, Single NucleotideReproducibility of ResultsExtracellular Matrix ProteinsUSH2A protein, humancopy number variationgenetic heterogeneity

Identifiers

PMID23897863
PMCPMC3745548
OpenAlexW1969232474

What OpenQuestion holds

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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.