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Xrare: a machine learning method jointly modeling phenotypes and genetic evidence for rare disease diagnosis.

Genetics in medicine : official journal of the American College of Medical Genetics | 2019

Despite the successful progress next-generation sequencing technologies has achieved in diagnosing the genetic cause of rare Mendelian diseases, the current diagnostic rate is still far from satisfactory because of heterogeneity, imprecision, and noise in disease phenotype descriptions and insufficient utilization of expert knowledge in clinical genetics. To overcome these difficulties, we present a novel method called Xrare for the prioritization of causative gene variants in rare disease diagnosis.

Pubmed ID: 30675030 RIS Download

Research resources used in this publication

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Additional research tools detected in this publication

Antibodies used in this publication

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Associated grants

  • Agency: NCI NIH HHS, United States
    Id: P20 CA096470
  • Agency: NHGRI NIH HHS, United States
    Id: P50 HG007735
  • Agency: NHGRI NIH HHS, United States
    Id: R01 HG007834

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This is a list of tools and resources that we have found mentioned in this publication.


ClinVar (tool)

RRID:SCR_006169

Archive of aggregated information about sequence variation and its relationship to human health. Provides reports of relationships among human variations and phenotypes along with supporting evidence. Submissions from clinical testing labs, research labs, locus-specific databases, expert panels and professional societies are welcome. Collects reports of variants found in patient samples, assertions made regarding their clinical significance, information about submitter, and other supporting data. Alleles described in submissions are mapped to reference sequences, and reported according to HGVS standard.

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DECIPHER (tool)

RRID:SCR_006552

Interactive database which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance. Used to enhance clinical diagnosis by retrieving information from bioinformatics resources relevant to the imbalance found in the patient. Contributing to the DECIPHER database is a Consortium, comprising an international community of academic departments of clinical genetics. Each center maintains control of its own patient data (which are password protected within the center''''s own DECIPHER project) until patient consent is given to allow anonymous genomic and phenotypic data to become freely viewable within Ensembl and other genome browsers. Once data are shared, consortium members are able to gain access to the patient report and contact each other to discuss patients of mutual interest, thus facilitating the delineation of new microdeletion and microduplication syndromes.

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ERIC (tool)

RRID:SCR_007644

ERIC is a resource of annotated enterobacterial genomes. Information is available and accessed through a open web portal uniting biological data and analysis tools. ERIC contains information on Escherichia, Shigella, Salmonella, Yersinia, and other microorgansims. ERIC has recently been moved over to PATRIC: The PATRIC BRC is now responsible for all bacterial species in the NIAID Category A-C Priority Pathogen lists for biodefense research, and pathogens causing emerging/reemerging infectious diseases. For ERIC users, we understand that the resource was valuable to your work. As such, we will be doing our very best to create a useful PATRIC resource to continue supporting your work. We realize that the transition will cause disruptions. However, it is a priority for us to work with established BRC users and communities to identify and prioritize our transition efforts. We have concentrated on the transfer of genomic data for this initial release. We anticipate adding new data, tools, and website features over the next several months. We look forward to working with you during the next 5 years.

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