NOTE:
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) tracks display data generated from several key curation activities related to gene-disease validity, dosage sensitivity, and variant pathogenicity. ClinGen is a National Institute of Health (NIH)-funded program dedicated to building a central resource that defines the clinical relevance of genes and variants for use in precision medicine and research. This is accomplished by harnessing the data from both research efforts and clinical genetic testing and using it to propel expert and machine-driven curation activities. ClinGen works closely with the National Center for Biotechnology Information (NCBI) of the National Library of Medicine (NLM) which distributes part of this information through its ClinVar database.
The available data tracks are:
A rating system is used to classify the evidence supporting or refuting dosage sensitivity for individual genes and regions, which takes into consideration the following criteria: number of causative mutations reported, patterns of inheritance, consistency of phenotype, evidence from large-scale case-control studies, mutational mechanisms, data from public genome variation databases, and expert consensus opinion.
The system is intended to be of a "dynamic nature", with regions being reevaluated periodically to incorporate emerging evidence. The evidence collected is displayed within a publicly available database. Evidence that haploinsufficiency or triplosensitivity of a gene is associated with a specific phenotype will aid in the interpretive assessment of CNVs including that gene.
-Structural Variants are shaded according to variant type, -red for CNV loss, blue -for CNV gain. -
-Mouseover on items indicates affected protein-coding genes, size of the variant, variant type, and -associated phenotype. When more than 2 genes are affected by a variant, the full -list can be obtained by clicking on the item and reading the details page. -
--All tracks can be filtered according to the size of the variant, variant type (loss or gain), and -clinical significance (benign or pathogenic). -
+Dosage Scores are used to classify the evidence of the supporting dosage sensitivity map:
Mouseover on items shows the supporting evidence of dosage sensitivity and respective scores. All tracks can be filtered according to the supporting evidence of dosage sensitivity.
These tracks are multi-view composite tracks that contain multiple data types (views). Each view within a track has separate display controls, as described here.
The raw data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may -be queried from our REST API. Please refer to our +be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.
Thank you to ClinGen and NCBI, especially Erin Rooney Riggs for technical coordination and consultation, and to Christopher Lee, Anna Benet-Pages, and Maximilian Haeussler of the Genome Browser team for engineering the track display.
Rehm HL, Berg JS, Brooks LD, Bustamante CD, Evans JP, Landrum MJ, Ledbetter DH, Maglott DR, Martin CL, Nussbaum RL et al. ClinGen--the Clinical Genome Resource. N Engl J Med. 2015 Jun 4;372(23):2235-42. PMID: 26014595; PMC: PMC4474187
Riggs ER, Church DM, Hanson K, Horner VL, Kaminsky EB, Kuhn RM, Wain KE, Williams ES, Aradhya S, Kearney HM et al. Towards an evidence-based process for the clinical interpretation of copy number variation. Clin Genet. 2012 May;81(5):403-12. PMID: 22097934; PMC: PMC5008023
Strande NT, Riggs ER, Buchanan AH, Ceyhan-Birsoy O, DiStefano M, Dwight SS, Goldstein J, Ghosh R, Seifert BA, Sneddon TP et al. Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource. Am J Hum Genet. 2017 Jun 1;100(6):895-906. PMID: 28552198; PMC: PMC5473734