ClinGen CNVs Track Settings
Clinical Genome Resource (ClinGen) CNVs   (All Phenotype and Literature tracks)

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 Pathogenic  Curated  CNVs  ClinGen CNVs: Curated Pathogenic   Data format 
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 Pathogenic  Submitted  Coverage  ClinGen CNVs: Pathogenic Loss Coverage   Data format 
 Uncertain  Submitted  CNVs  ClinGen CNVs: Uncertain   Data format 

Note: ClinGen CNV data are now updated on ClinVar Variants track. See news archive for details.

The ClinGen CNVs track is no longer being updated. These data, along with updates, can be found in the ClinVar Copy Number Variants (ClinVar CNVs) track.

See our news archive for more information.


These data are for research purposes only. While the ClinGen data are open to the public, users seeking information about a personal medical or genetic condition are urged to consult with a qualified physician for diagnosis and for answers to personal medical questions.

UCSC presents these data for use by qualified professionals, and even such professionals should use caution in interpreting the significance of information found here. No single data point should be taken at face value and such data should always be used in conjunction with as much corroborating data as possible. No treatment protocols should be developed or patient advice given on the basis of these data without careful consideration of all possible sources of information.

No attempt to identify individual patients should be undertaken. No one is authorized to attempt to identify patients by any means.

The Clinical Genome Resource (ClinGen) is a National Institutes of Health (NIH)-funded program dedicated to building a genomic knowledge base to improve patient care. This will be accomplished by harnessing the data from both research efforts and clinical genetic testing, and using it to propel expert and machine-driven curation activities. By facilitating collaboration within the genomics community, we will all better understand the relationship between genomic variation and human health. ClinGen will work closely with the National Center for Biotechnology Information (NCBI) of the National Library of Medicine (NLM), which will distribute this information through its ClinVar database.

The ClinGen dataset displays clinical microarray data submitted to dbGaP/dbVar at NCBI by ClinGen member laboratories (dbVar study nstd37), as well as clinical data reported in Kaminsky et al., 2011 (dbVar study ntsd101) (see reference below). This track shows copy number variants (CNVs) found in patients referred for genetic testing for indications such as intellectual disability, developmental delay, autism and congenital anomalies. Additionally, the ClinGen "Curated Pathogenic" and "Curated Benign" tracks represent genes/genomic regions reviewed for dosage sensitivity in an evidence-based manner by the ClinGen Structural Variation Working Group (dbVar study nstd45).

The CNVs in this study have been reviewed for their clinical significance by the submitting ClinGen laboratory. Some of the deletions and duplications in the track have been reported as causative for a phenotype by the submitting clinical laboratory; this information was based on current knowledge at the time of submission. However, it should be noted that phenotype information is often vague and imprecise and should be used with caution. While all samples were submitted because of a phenotype in a patient, only 15% of patients had variants determined to be causal, and most patients will have additional variants that are not causal.

CNVs are separated into subtracks and are labeled as:

  • Pathogenic
  • Uncertain: Likely Pathogenic
  • Uncertain
  • Uncertain: Likely Benign
  • Benign
The user should be aware that some of the data were submitted using a 3-class system, with the two "Likely" categories omitted.

Two subtracks, "Path Gain" and "Path Loss", are aggregate tracks showing graphically the accumulated level of gains and losses in the Pathogenic subtrack across the genome. Similarly, "Benign Gain" and "Benign Loss" show the accumulated level of gains and losses in the Benign subtrack. These tracks are collectively called "Coverage" tracks.

Many samples have multiple variants, not all of which are causative of the phenotype. The CNVs in these samples have been decoupled, so it is not possible to connect multiple imbalances as coming from a single patient. It is therefore not possible to identify individuals via their genotype.

Methods and Color Convention

The samples were analyzed by arrays from patients referred for cytogenetic testing due to clinical phenotypes. Samples were analyzed with a probe spacing of 20-75 kb. The minimum CNV breakpoints are shown; if available, the maximum CNV breakpoints are provided in the details page, but are not shown graphically on the Browser image.

Data were submitted to dbGaP at NCBI and thence decoupled as described into dbVar for unrestricted release.

The entries are colored red for loss and blue for gain. The names of items use the ClinVar convention of appending "_inheritance" indicating the mechanism of inheritance, if known: "_pat, _mat, _dnovo, _unk" as paternal, maternal, de novo and unknown, respectively.


Most data were validated by the submitting laboratory using various methods, including FISH, G-banded karyotype, MLPA and qPCR.


Thank you to ClinGen and NCBI for technical coordination and consultation, and to the UCSC Genome Browser staff for engineering the track display.


Miller DT, Adam MP, Aradhya S, Biesecker LG, Brothman AR, Carter NP, Church DM, Crolla JA, Eichler EE, Epstein CJ et al. Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet. 2010 May 14;86(5):749-64. PMID: 20466091; PMC: PMC2869000

Kaminsky EB, Kaul V, Paschall J, Church DM, Bunke B, Kunig D, Moreno-De-Luca D, Moreno-De-Luca A, Mulle JG, Warren ST et al. An evidence-based approach to establish the functional and clinical significance of copy number variants in intellectual and developmental disabilities. Genet Med. 2011 Sep;13(9):777-84. PMID: 21844811; PMC: PMC3661946