Nucleic Acids Research
The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data
The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.
The Database of Genotypes and Phenotypes (dbGap, http://www.ncbi.nlm.nih.gov/gap) is a National Institutes of Health-sponsored repository charged to archive, curate and distribute information produced by studies investigating the interaction of genotype and phenotype. Information in dbGaP is organized as a hierarchical structure and includes the accessioned objects, phenotypes (as variables and datasets), various molecular assay data (SNP and Expression Array data, Sequence and Epigenomic marks), analyses and documents. Publicly accessible metadata about submitted studies, summary level data, and documents related to studies can be accessed freely on the dbGaP website. Individual-level data are accessible via Controlled Access application to scientists across the globe.
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.
The Database of Genomic Variants: a curated collection of structural variation in the human genome
Over the past decade, the Database of Genomic Variants (DGV; http://dgv.tcag.ca/) has provided a publicly accessible, comprehensive curated catalogue of structural variation (SV) found in the genomes of control individuals from worldwide populations. Here, we describe updates and new features, which have expanded the utility of DGV for both the basic research and clinical diagnostic communities. The current version of DGV consists of 55 published studies, comprising >2.5 million entries identified in >22 300 genomes. Studies included in DGV are selected from the accessioned data sets in the archival SV databases dbVar (NCBI) and DGVa (EBI), and then further curated for accuracy and validity. The core visualization tool (gbrowse) has been upgraded with additional functions to facilitate data analysis and comparison, and a new query tool has been developed to provide flexible and interactive access to the data. The content from DGV is regularly incorporated into other large-scale genome reference databases and represents a standard data resource for new product and database development, in particular for copy number variation testing in clinical labs. The accurate cataloguing of variants in DGV will continue to enable medical genetics and genome sequencing research.
DECIPHER: database for the interpretation of phenotype-linked plausibly pathogenic sequence and copy-number variation
The DECIPHER database (https://decipher.sanger.ac.uk/) is an accessible online repository of genetic variation with associated phenotypes that facilitates the identification and interpretation of pathogenic genetic variation in patients with rare disorders. Contributing to DECIPHER is an international consortium of >200 academic clinical centres of genetic medicine and ≥1600 clinical geneticists and diagnostic laboratory scientists. Information integrated from a variety of bioinformatics resources, coupled with visualization tools, provides a comprehensive set of tools to identify other patients with similar genotype–phenotype characteristics and highlights potentially pathogenic genes. In a significant development, we have extended DECIPHER from a database of just copy-number variants to allow upload, annotation and analysis of sequence variants such as single nucleotide variants (SNVs) and InDels. Other notable developments in DECIPHER include a purpose-built, customizable and interactive genome browser to aid combined visualization and interpretation of sequence and copy-number variation against informative datasets of pathogenic and population variation. We have also introduced several new features to our deposition and analysis interface. This article provides an update to the DECIPHER database, an earlier instance of which has been described elsewhere [Swaminathan et al. (2012) DECIPHER: web-based, community resource for clinical interpretation of rare variants in developmental disorders. Hum. Mol. Genet., 21, R37–R44].
The National Human Genome Research Institute (NHGRI) Catalog of Published Genome-Wide Association Studies (GWAS) Catalog provides a publicly available manually curated collection of published GWAS assaying at least 100 000 single-nucleotide polymorphisms (SNPs) and all SNP-trait associations with P <1 x 10–5. The Catalog includes 1751 curated publications of 11 912 SNPs. In addition to the SNP-trait association data, the Catalog also publishes a quarterly diagram of all SNP-trait associations mapped to the SNPs’ chromosomal locations. The Catalog can be accessed via a tabular web interface, via a dynamic visualization on the human karyotype, as a downloadable tab-delimited file and as an OWL knowledge base. This article presents a number of recent improvements to the Catalog, including novel ways for users to interact with the Catalog and changes to the curation infrastructure.
We have developed Lynx (http://lynx.ci.uchicago.edu)—a web-based database and a knowledge extraction engine, supporting annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Its underlying knowledge base (LynxKB) integrates various classes of information from >35 public databases and private collections, as well as manually curated data from our group and collaborators. Lynx provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization to assist the user in extracting meaningful knowledge from LynxKB and experimental data, whereas its service-oriented architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.
NECTAR (Non-synonymous Enriched Coding muTation ARchive; http://nectarmutation.org) is a database and web application to annotate disease-related and functionally important amino acids in human proteins. A number of tools are available to facilitate the interpretation of DNA variants identified in diagnostic or research sequencing. These typically identify previous reports of DNA variation at a given genomic location, predict its effects on transcript and protein sequence and may predict downstream functional consequences. Previous reports and functional annotations are typically linked by the genomic location of the variant observed. NECTAR collates disease-causing variants and functionally important amino acid residues from a number of sources. Importantly, rather than simply linking annotations by a shared genomic location, NECTAR annotates variants of interest with details of previously reported variation affecting the same codon. This provides a much richer data set for the interpretation of a novel DNA variant. NECTAR also identifies functionally equivalent amino acid residues in evolutionarily related proteins (paralogues) and, where appropriate, transfers annotations between them. As well as accessing these data through a web interface, users can upload batches of variants in variant call format (VCF) for annotation on-the-fly. The database is freely available to download from the ftp site: ftp://ftp.nectarmutation.org.
Developments in FINDbase worldwide database for clinically relevant genomic variation allele frequencies
FINDbase (http://www.findbase.org) aims to document frequencies of clinically relevant genomic variations, namely causative mutations and pharmacogenomic markers, worldwide. Each database record includes the population, ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related databases and the genetic variation together with its frequency in that population. Here, we report, in addition to the regular data content updates, significant developments in FINDbase, related to data visualization and querying, data submission, interrelation with other resources and a new module for genetic disease summaries. In particular, (i) we have developed new data visualization tools that facilitate data querying and comparison among different populations, (ii) we have generated a new FINDbase module, built around Microsoft’s PivotViewer (http://www.getpivot.com) software, based on Microsoft Silverlight technology (http://www.silverlight.net), that includes 259 genetic disease summaries from five populations, systematically collected from the literature representing the documented genetic makeup of these populations and (iii) the implementation of a generic data submission tool for every module currently available in FINDbase.
InvFEST, a database integrating information of polymorphic inversions in the human genome
The newest genomic advances have uncovered an unprecedented degree of structural variation throughout genomes, with great amounts of data accumulating rapidly. Here we introduce InvFEST (http://invfestdb.uab.cat), a database combining multiple sources of information to generate a complete catalogue of non-redundant human polymorphic inversions. Due to the complexity of this type of changes and the underlying high false-positive discovery rate, it is necessary to integrate all the available data to get a reliable estimate of the real number of inversions. InvFEST automatically merges predictions into different inversions, refines the breakpoint locations, and finds associations with genes and segmental duplications. In addition, it includes data on experimental validation, population frequency, functional effects and evolutionary history. All this information is readily accessible through a complete and user-friendly web report for each inversion. In its current version, InvFEST combines information from 34 different studies and contains 1092 candidate inversions, which are categorized based on internal scores and manual curation. Therefore, InvFEST aims to represent the most reliable set of human inversions and become a central repository to share information, guide future studies and contribute to the analysis of the functional and evolutionary impact of inversions on the human genome.
In recent years, human regulatory SNPs (rSNPs) have been widely studied. Here, we present database rSNPBase, freely available at http://rsnp.psych.ac.cn/, to provide curated rSNPs that analyses the regulatory features of all SNPs in the human genome with reference to experimentally supported regulatory elements. In contrast with previous SNP functional annotation databases, rSNPBase is characterized by several unique features. (i) To improve reliability, all SNPs in rSNPBase are annotated with reference to experimentally supported regulatory elements. (ii) rSNPBase focuses on rSNPs involved in a wide range of regulation types, including proximal and distal transcriptional regulation and post-transcriptional regulation, and identifies their potentially regulated genes. (iii) Linkage disequilibrium (LD) correlations between SNPs were analysed so that the regulatory feature is annotated to SNP-set rather than a single SNP. (iv) rSNPBase provides the spatio-temporal labels and experimental eQTL labels for SNPs. In summary, rSNPBase provides more reliable, comprehensive and user-friendly regulatory annotations on rSNPs and will assist researchers in selecting candidate SNPs for further genetic studies and in exploring causal SNPs for in-depth molecular mechanisms of complex phenotypes.
canSAR (http://cansar.icr.ac.uk) is a public integrative cancer-focused knowledgebase for the support of cancer translational research and drug discovery. Through the integration of biological, pharmacological, chemical, structural biology and protein network data, it provides a single information portal to answer complex multidisciplinary questions including—among many others—what is known about a protein, in which cancers is it expressed or mutated, and what chemical tools and cell line models can be used to experimentally probe its activity? What is known about a drug, its cellular sensitivity profile and what proteins is it known to bind that may explain unusual bioactivity? Here we describe major enhancements to canSAR including new data, improved search and browsing capabilities and new target, cancer cell line, protein family and 3D structure summaries and tools.
Exome sequencing (exome-seq) has aided in the discovery of a huge amount of mutations in cancers, yet challenges remain in converting oncogenomics data into information that is interpretable and accessible for clinical care. We constructed DriverDB (http://ngs.ym.edu.tw/driverdb/), a database which incorporates 6079 cases of exome-seq data, annotation databases (such as dbSNP, 1000 Genome and Cosmic) and published bioinformatics algorithms dedicated to driver gene/mutation identification. We provide two points of view, ‘Cancer’ and ‘Gene’, to help researchers to visualize the relationships between cancers and driver genes/mutations. The ‘Cancer’ section summarizes the calculated results of driver genes by eight computational methods for a specific cancer type/dataset and provides three levels of biological interpretation for realization of the relationships between driver genes. The ‘Gene’ section is designed to visualize the mutation information of a driver gene in five different aspects. Moreover, a ‘Meta-Analysis’ function is provided so researchers may identify driver genes in customer-defined samples. The novel driver genes/mutations identified hold potential for both basic research and biotech applications.
DNA copy number aberrations (CNAs) can be found in the majority of cancer genomes and are crucial for understanding the potential mechanisms underlying tumor initiation and progression. Since the first release in 2001, the Progenetix project (http://www.progenetix.org) has provided a reference resource dedicated to provide the most comprehensive collection of genome-wide CNA profiles. Reflecting the application of comparative genomic hybridization techniques to tens of thousands of cancer genomes, over the past 12 years our data curation efforts have resulted in a more than 60-fold increase in the number of cancer samples presented through Progenetix. In addition, new data exploration tools and visualization options have been added. In particular, the gene-specific CNA frequency analysis should facilitate the assignment of cancer genes to related cancer types. In addition, the new user file processing interface allows users to take advantage of the online tools, including various data representation options for proprietary data pre-publication. In this update article, we report recent improvements of the database in terms of content, user interface and online tools.
HbVar (http://globin.bx.psu.edu/hbvar) is one of the oldest and most appreciated locus-specific databases launched in 2001 by a multi-center academic effort to provide timely information on the genomic alterations leading to hemoglobin variants and all types of thalassemia and hemoglobinopathies. Database records include extensive phenotypic descriptions, biochemical and hematological effects, associated pathology and ethnic occurrence, accompanied by mutation frequencies and references. Here, we report updates to >600 HbVar entries, inclusion of population-specific data for 28 populations and 27 ethnic groups for α-, and β-thalassemias and additional querying options in the HbVar query page. HbVar content was also inter-connected with two other established genetic databases, namely FINDbase (http://www.findbase.org) and Leiden Open-Access Variation database (http://www.lovd.nl), which allows comparative data querying and analysis. HbVar data content has contributed to the realization of two collaborative projects to identify genomic variants that lie on different globin paralogs. Most importantly, HbVar data content has contributed to demonstrate the microattribution concept in practice. These updates significantly enriched the database content and querying potential, enhanced the database profile and data quality and broadened the inter-relation of HbVar with other databases, which should increase the already high impact of this resource to the globin and genetic database community.
HMDD v2.0: a database for experimentally supported human microRNA and disease associations
The Human microRNA Disease Database (HMDD; available via the Web site at http://cmbi.bjmu.edu.cn/hmdd and http://18.104.22.168/hmdd/tools/hmdd2.html) is a collection of experimentally supported human microRNA (miRNA) and disease associations. Here, we describe the HMDD v2.0 update that presented several novel options for users to facilitate exploration of the data in the database. In the updated database, miRNA–disease association data were annotated in more details. For example, miRNA–disease association data from genetics, epigenetics, circulating miRNAs and miRNA–target interactions were integrated into the database. In addition, HMDD v2.0 presented more data that were generated based on concepts derived from the miRNA–disease association data, including disease spectrum width of miRNAs and miRNA spectrum width of human diseases. Moreover, we provided users a link to download all the data in the HMDD v2.0 and a link to submit novel data into the database. Meanwhile, we also maintained the old version of HMDD. By keeping data sets up-to-date, HMDD should continue to serve as a valuable resource for investigating the roles of miRNAs in human disease.
PubChem BioAssay: 2014 update
PubChem’s BioAssay database (http://pubchem.ncbi.nlm.nih.gov) is a public repository for archiving biological tests of small molecules generated through high-throughput screening experiments, medicinal chemistry studies, chemical biology research and drug discovery programs. In addition, the BioAssay database contains data from high-throughput RNA interference screening aimed at identifying critical genes responsible for a biological process or disease condition. The mission of PubChem is to serve the community by providing free and easy access to all deposited data. To this end, PubChem BioAssay is integrated into the National Center for Biotechnology Information retrieval system, making them searchable by Entrez queries and cross-linked to other biomedical information archived at National Center for Biotechnology Information. Moreover, PubChem BioAssay provides web-based and programmatic tools allowing users to search, access and analyze bioassay test results and metadata. In this work, we provide an update for the PubChem BioAssay resource, such as information content growth, new developments supporting data integration and search, and the recently deployed PubChem Upload to streamline chemical structure and bioassay submissions.
The ChEMBL bioactivity database: an update
ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 Nucleic Acids Research Database Issue. Since then, a variety of new data sources and improvements in functionality have contributed to the growth and utility of the resource. In particular, more comprehensive tracking of compounds from research stages through clinical development to market is provided through the inclusion of data from United States Adopted Name applications; a new richer data model for representing drug targets has been developed; and a number of methods have been put in place to allow users to more easily identify reliable data. Finally, access to ChEMBL is now available via a new Resource Description Framework format, in addition to the web-based interface, data downloads and web services.
DrugBank (http://www.drugbank.ca) is a comprehensive online database containing extensive biochemical and pharmacological information about drugs, their mechanisms and their targets. Since it was first described in 2006, DrugBank has rapidly evolved, both in response to user requests and in response to changing trends in drug research and development. Previous versions of DrugBank have been widely used to facilitate drug and in silico drug target discovery. The latest update, DrugBank 4.0, has been further expanded to contain data on drug metabolism, absorption, distribution, metabolism, excretion and toxicity (ADMET) and other kinds of quantitative structure activity relationships (QSAR) information. These enhancements are intended to facilitate research in xenobiotic metabolism (both prediction and characterization), pharmacokinetics, pharmacodynamics and drug design/discovery. For this release, >1200 drug metabolites (including their structures, names, activity, abundance and other detailed data) have been added along with >1300 drug metabolism reactions (including metabolizing enzymes and reaction types) and dozens of drug metabolism pathways. Another 30 predicted or measured ADMET parameters have been added to each DrugCard, bringing the average number of quantitative ADMET values for Food and Drug Administration-approved drugs close to 40. Referential nuclear magnetic resonance and MS spectra have been added for almost 400 drugs as well as spectral and mass matching tools to facilitate compound identification. This expanded collection of drug information is complemented by a number of new or improved search tools, including one that provides a simple analyses of drug–target, –enzyme and –transporter associations to provide insight on drug–drug interactions.
The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands
The International Union of Basic and Clinical Pharmacology/British Pharmacological Society (IUPHAR/BPS) Guide to PHARMACOLOGY (http://www.guidetopharmacology.org) is a new open access resource providing pharmacological, chemical, genetic, functional and pathophysiological data on the targets of approved and experimental drugs. Created under the auspices of the IUPHAR and the BPS, the portal provides concise, peer-reviewed overviews of the key properties of a wide range of established and potential drug targets, with in-depth information for a subset of important targets. The resource is the result of curation and integration of data from the IUPHAR Database (IUPHAR-DB) and the published BPS ‘Guide to Receptors and Channels’ (GRAC) compendium. The data are derived from a global network of expert contributors, and the information is extensively linked to relevant databases, including ChEMBL, DrugBank, Ensembl, PubChem, UniProt and PubMed. Each of the ~6000 small molecule and peptide ligands is annotated with manually curated 2D chemical structures or amino acid sequences, nomenclature and database links. Future expansion of the resource will complete the coverage of all the targets of currently approved drugs and future candidate targets, alongside educational resources to guide scientists and students in pharmacological principles and techniques.