ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/) provides a freely available archive of reports of relationships among medically important variants and phenotypes. ClinVar accessions submissions reporting human variation, interpretations of the relationship of that variation to human health and the evidence supporting each interpretation. The database is tightly coupled with dbSNP and dbVar, which maintain information about the location of variation on human assemblies. ClinVar is also based on the phenotypic descriptions maintained in MedGen (http://www.ncbi.nlm.nih.gov/medgen). Each ClinVar record represents the submitter, the variation and the phenotype, i.e. the unit that is assigned an accession of the format SCV000000000.0. The submitter can update the submission at any time, in which case a new version is assigned. To facilitate evaluation of the medical importance of each variant, ClinVar aggregates submissions with the same variation/phenotype combination, adds value from other NCBI databases, assigns a distinct accession of the format RCV000000000.0 and reports if there are conflicting clinical interpretations. Data in ClinVar are available in multiple formats, including html, download as XML, VCF or tab-delimited subsets. Data from ClinVar are provided as annotation tracks on genomic RefSeqs and are used in tools such as Variation Reporter (http://www.ncbi.nlm.nih.gov/variation/tools/reporter), which reports what is known about variation based on user-supplied locations.

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ClinVar: public archive of relationships among sequence variation and human phenotype

Hypertension 66 (20.3%) 24 (24.2%) 30 (16.3%) NS Diabetes 20 (6.2%) 7 (7.1%) 10 (5.4%) NS Excess weight 78 (24%) 27 (27.3%) 44 (23.9%) NS Smokers 64 (19.7%) 17 (17.2%) 35 (19.0%) NS Age >50 years 137 (42.2%) 54 (54.5%) 67 (36.4%) <0.02 Kidney disease 7 (2.2%) 1 (1%) 5 (2.7%) NS Family history, DM 102 (31.4%) 28 (28.3%) 66 (35.9%) NS

Conflict of interest statement. None declared.

One of the most pressing challenges in genomic medicine is to understand the role played by genetic variation in health and disease. Thanks to the exploration of genomic variants at large scale, hundreds of thousands of disease-associated loci have been uncovered. However, the identification of variants of clinical relevance is a significant challenge that requires comprehensive interrogation of previous knowledge and linkage to new experimental results. To assist in this complex task, we created DisGeNET (http://www.disgenet.org/), a knowledge management platform integrating and standardizing data about disease associated genes and variants from multiple sources, including the scientific literature. DisGeNET covers the full spectrum of human diseases as well as normal and abnormal traits. The current release covers more than 24 000 diseases and traits, 17 000 genes and 117 000 genomic variants. The latest developments of DisGeNET include new sources of data, novel data attributes and prioritization metrics, a redesigned web interface and recently launched APIs. Thanks to the data standardization, the combination of expert curated information with data automatically mined from the scientific literature, and a suite of tools for accessing its publicly available data, DisGeNET is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.

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The DisGeNET knowledge platform for disease genomics: 2019 update.

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of annotated genomic, transcript and protein sequence records derived from data in public sequence archives and from computation, curation and collaboration (http://wwwncbinlmnihgov/refseq/) We report here on growth of the mammalian and human subsets, changes to NCBI’s eukaryotic annotation pipeline and modifications affecting transcript and protein records Recent changes to NCBI’s eukaryotic genome annotation pipeline provide higher throughput, and the addition of RNAseq data to the pipeline results in a significant expansion of the number of transcripts and novel exons annotated on mammalian RefSeq genomes Recent annotation changes include reporting supporting evidence for transcript records, modification of exon feature annotation and the addition of a structured report of gene and sequence attributes of biological interest We also describe a revised protein annotation policy for alternatively spliced transcripts with more divergent predicted proteins and we summarize the current status of the RefSeqGene project

RefSeq: an update on mammalian reference sequences

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1 In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals) These rare variants provide insights into mutational processes and recent human evolutionary history The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 001% The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history

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Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant ('provider interpretation') or from groups such as patient registries that primarily provide phenotypic information from patients ('phenotyping only'). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.

/pdf/clinvar-improving-access-to-variant-interpretations-and-4rcjjp3d7w.pdf

ClinVar: improving access to variant interpretations and supporting evidence.

The National Institutes of Health Genetic Testing Registry (GTR; available online at http://www.ncbi.nlm.nih.gov/gtr/) maintains comprehensive information about testing offered worldwide for disorders with a genetic basis. Information is voluntarily submitted by test providers. The database provides details of each test (e.g. its purpose, target populations, methods, what it measures, analytical validity, clinical validity, clinical utility, ordering information) and laboratory (e.g. location, contact information, certifications and licenses). Each test is assigned a stable identifier of the format GTR000000000, which is versioned when the submitter updates information. Data submitted by test providers are integrated with basic information maintained in National Center for Biotechnology Information's databases and presented on the web and through FTP (ftp.ncbi.nih.gov/pub/GTR/_README.html).

The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency

Medical Genetics Summaries

Medical Genetics Summaries is a growing collection of summaries which describe the impact that specific sequence variations have on health. The summaries review genetic variants that underlie inherited conditions, affect the risk of developing a disease in the future, or influence how an individual may respond to a specific drug.

Malheiro Aj

Papers

ClinVar: improving access to variant interpretations and supporting evidence.

The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency

Medical Genetics Summaries

Medical Genetics Summaries [Internet]

Allopurinol Therapy and HLA-B*58:01 Genotype -- Medical Genetics Summaries