Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

Expression Atlas update: insights from sequencing data at both bulk and single cell level

Expression Atlas (www.ebi.ac.uk/gxa) and its newest counterpart the Single Cell Expression Atlas (www.ebi.ac.uk/gxa/sc) are EMBL-EBI's knowledgebases for gene and protein expression and localisation in bulk and at single cell level. These resources aim to allow users to investigate their expression in normal tissue (baseline) or in response to perturbations such as disease or changes to genotype (differential) across multiple species. Users are invited to search for genes or metadata terms across species or biological conditions in a standardised consistent interface. Alongside these data, new features in Single Cell Expression Atlas allow users to query metadata through our new cell type wheel search. At the experiment level data can be explored through two types of dimensionality reduction plots, t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP), overlaid with either clustering or metadata information to assist users' understanding. Data are also visualised as marker gene heatmaps identifying genes that help confer cluster identity. For some data, additional visualisations are available as interactive cell level anatomograms and cell type gene expression heatmaps.

The European Nucleotide Archive in 2023

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena) is maintained by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI). The ENA is one of the three members of the International Nucleotide Sequence Database Collaboration (INSDC). It serves the bioinformatics community worldwide via the submission, processing, archiving and dissemination of sequence data. The ENA supports data types ranging from raw reads, through alignments and assemblies to functional annotation. The data is enriched with contextual information relating to samples and experimental configurations. In this article, we describe recent progress and improvements to ENA services. In particular, we focus upon three areas of work in 2023: FAIRness of ENA data, pandemic preparedness and foundational technology. For FAIRness, we have introduced minimal requirements for spatiotemporal annotation, created a metadata-based classification system, incorporated third party metadata curations with archived records, and developed a new rapid visualisation platform, the ENA Notebooks. For foundational enhancements, we have improved the INSDC data exchange and synchronisation pipelines, and invested in site reliability engineering for ENA infrastructure. In order to support genomic surveillance efforts, we have continued to provide ENA services in support of SARS-CoV-2 data mobilisation and have adapted these for broader pathogen surveillance efforts.

Toward a common standard for data and specimen provenance in life sciences

Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and knowledge derived is thus significantly influenced by the quality of the samples, the experimental methods, and the data analysis. Therefore, a comprehensive and precise documentation of the pre-analytical conditions, the analytical procedures, and the data processing are essential to be able to assess the validity of the research results. With the increasing importance of the exchange, reuse, and sharing of data and samples, procedures are required that enable cross-organizational documentation, traceability, and non-repudiation. At present, this information on the provenance of samples and data is mostly either sparse, incomplete, or incoherent. Since there is no uniform framework, this information is usually only provided within the organization and not interoperably. At the same time, the collection and sharing of biological and environmental specimens increasingly require definition and documentation of benefit sharing and compliance to regulatory requirements rather than consideration of pure scientific needs. In this publication, we present an ongoing standardization effort to provide trustworthy machine-actionable documentation of the data lineage and specimens. We would like to invite experts from the biotechnology and biomedical fields to further contribute to the standard.

The Translational Data Catalog - discoverable biomedical datasets

The discoverability of datasets resulting from the diverse range of translational and biomedical projects remains sporadic. It is especially difficult for datasets emerging from pre-competitive projects, often due to the legal constraints of data-sharing agreements, and the different priorities of the private and public sectors. The Translational Data Catalog is a single discovery point for the projects and datasets produced by a number of major research programmes funded by the European Commission. Funded by and rooted in a number of these European private-public partnership projects, the Data Catalog is built on FAIR-enabling community standards, and its mission is to ensure that datasets are findable and accessible by machines. Here we present its creation, content, value and adoption, as well as the next steps for sustainability within the ELIXIR ecosystem.

MGnify Genomes: A Resource for Biome-specific Microbial Genome Catalogues

An increasingly common output arising from the analysis of shotgun metagenomic datasets is the generation of metagenome-assembled genomes (MAGs), with tens of thousands of MAGs now described in the literature. However, the discovery and comparison of these MAG collections is hampered by the lack of uniformity in their generation, annotation and storage. To address this, we have developed MGnify Genomes, a growing collection of biome-specific non-redundant microbial genome catalogues generated using MAGs and publicly available isolate genomes. Genomes within a biome-specific catalogue are organised into species clusters. For species that contain multiple conspecific genomes, the highest quality genome is selected as the representative, always prioritising an isolate genome over a MAG. The species representative sequences and annotations can be visualised on the MGnify website and the full catalogue and associated analysis outputs can be downloaded from MGnify servers. A suite of online search tools is provided allowing users to compare their own sequences, ranging from a gene to sets of genomes, against the catalogues. Seven biomes are available currently, comprising over 300,000 genomes that represent 11,048 non-redundant species, and include 36 taxonomic classes not currently represented by cultured genomes. MGnify Genomes is available at https://www.ebi.ac.uk/metagenomics/browse/genomes/.

FAIR in action - a flexible framework to guide FAIRification

The COVID-19 pandemic has highlighted the need for FAIR (Findable, Accessible, Interoperable, and Reusable) data more than any other scientific challenge to date. We developed a flexible, multi-level, domain-agnostic FAIRification framework, providing practical guidance to improve the FAIRness for both existing and future clinical and molecular datasets. We validated the framework in collaboration with several major public-private partnership projects, demonstrating and delivering improvements across all aspects of FAIR and across a variety of datasets and their contexts. We therefore managed to establish the reproducibility and far-reaching applicability of our approach to FAIRification tasks.

The FAIR Cookbook - the essential resource for and by FAIR doers

The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good data stewardship and a prerequisite for reproducibility. Nowadays, FAIR guides data policy actions and professional practices in the public and private sectors. Despite such global endorsements, however, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an open, online resource of hands-on recipes for "FAIR doers" in the Life Sciences. Created by researchers and data managers professionals in academia, (bio)pharmaceutical companies and information service industries, the FAIR Cookbook covers the key steps in a FAIRification journey, the levels and indicators of FAIRness, the maturity model, the technologies, the tools and the standards available, as well as the skills required, and the challenges to achieve and improve data FAIRness. Part of the ELIXIR ecosystem, and recommended by funders, the FAIR Cookbook is open to contributions of new recipes.

Toward a data infrastructure for the Plant Cell Atlas

We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms. The Human Cell Atlas has developed an extensive infrastructure for human and mouse single cell data, while the European Bioinformatics Institute has developed a Single Cell Expression Atlas, that currently houses several plant data sets. We discuss issues related to appropriate ontologies for describing a plant single cell experiment. We imagine how such an infrastructure will enable biologists and data scientists to glean new insights into plant biology in the coming decades, as long as such data are made accessible to the community in an open manner.

MGnify: the microbiome sequence data analysis resource in 2023

The MGnify platform (https://www.ebi.ac.uk/metagenomics) facilitates the assembly, analysis and archiving of microbiome-derived nucleic acid sequences. The platform provides access to taxonomic assignments and functional annotations for nearly half a million analyses covering metabarcoding, metatranscriptomic, and metagenomic datasets, which are derived from a wide range of different environments. Over the past 3 years, MGnify has not only grown in terms of the number of datasets contained but also increased the breadth of analyses provided, such as the analysis of long-read sequences. The MGnify protein database now exceeds 2.4 billion non-redundant sequences predicted from metagenomic assemblies. This collection is now organised into a relational database making it possible to understand the genomic context of the protein through navigation back to the source assembly and sample metadata, marking a major improvement. To extend beyond the functional annotations already provided in MGnify, we have applied deep learning-based annotation methods. The technology underlying MGnify's Application Programming Interface (API) and website has been upgraded, and we have enabled the ability to perform downstream analysis of the MGnify data through the introduction of a coupled Jupyter Lab environment.

The European Nucleotide Archive in 2022

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena), maintained by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), offers those producing data an open and supported platform for the management, archiving, publication, and dissemination of data; and to the scientific community as a whole, it offers a globally comprehensive data set through a host of data discovery and retrieval tools. Here, we describe recent updates to the ENA's submission and retrieval services as well as focused efforts to improve connectivity, reusability, and interoperability of ENA data and metadata.

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

BACKGROUND

No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge.

METHODS

The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing.

FINDINGS

2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters.

INTERPRETATION

The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

FUNDING

UK Research and Innovation and National Institute for Health Research.

ELIXIR biovalidator for semantic validation of life science metadata

SUMMARY

To advance biomedical research, increasingly large amounts of complex data need to be discovered and integrated. This requires syntactic and semantic validation to ensure shared understanding of relevant entities. This article describes the ELIXIR biovalidator, which extends the syntactic validation of the widely used AJV library with ontology-based validation of JSON documents.

AVAILABILITY AND IMPLEMENTATION

Source code: https://github.com/elixir-europe/biovalidator, Release: v1.9.1, License: Apache License 2.0, Deployed at: https://www.ebi.ac.uk/biosamples/schema/validator/validate.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Expression Atlas update: gene and protein expression in multiple species

The EMBL-EBI Expression Atlas is an added value knowledge base that enables researchers to answer the question of where (tissue, organism part, developmental stage, cell type) and under which conditions (disease, treatment, gender, etc) a gene or protein of interest is expressed. Expression Atlas brings together data from >4500 expression studies from >65 different species, across different conditions and tissues. It makes these data freely available in an easy to visualise form, after expert curation to accurately represent the intended experimental design, re-analysed via standardised pipelines that rely on open-source community developed tools. Each study's metadata are annotated using ontologies. The data are re-analyzed with the aim of reproducing the original conclusions of the underlying experiments. Expression Atlas is currently divided into Bulk Expression Atlas and Single Cell Expression Atlas. Expression Atlas contains data from differential studies (microarray and bulk RNA-Seq) and baseline studies (bulk RNA-Seq and proteomics), whereas Single Cell Expression Atlas is currently dedicated to Single Cell RNA-Sequencing (scRNA-Seq) studies. The resource has been in continuous development since 2009 and it is available at https://www.ebi.ac.uk/gxa.

The European Nucleotide Archive in 2021

The European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena), maintained at the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) provides freely accessible services, both for deposition of, and access to, open nucleotide sequencing data. Open scientific data are of paramount importance to the scientific community and contribute daily to the acceleration of scientific advance. Here, we outline the major updates to ENA’s services and infrastructure that have been delivered over the past year.

The Data Use Ontology to streamline responsible access to human biomedical datasets

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide.

GA4GH: International policies and standards for data sharing across genomic research and healthcare

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

BioSamples database: FAIRer samples metadata to accelerate research data management

The BioSamples database at EMBL-EBI is the central institutional repository for sample metadata storage and connection to EMBL-EBI archives and other resources. The technical improvements to our infrastructure described in our last update have enabled us to scale and accommodate an increasing number of communities, resulting in a higher number of submissions and more heterogeneous data. The BioSamples database now has a valuable set of features and processes to improve data quality in BioSamples, and in particular enriching metadata content and following FAIR principles. In this manuscript, we describe how BioSamples in 2021 handles requirements from our community of users through exemplar use cases: increased findability of samples and improved data management practices support the goals of the ReSOLUTE project, how the plant community benefits from being able to link genotypic to phenotypic information, and we highlight how cumulatively those improvements contribute to more complex multi-omics data integration supporting COVID-19 research. Finally, we present underlying technical features used as pillars throughout those use cases and how they are reused for expanded engagement with communities such as FAIRplus and the Global Alliance for Genomics and Health. Availability: The BioSamples database is freely available at http://www.ebi.ac.uk/biosamples. Content is distributed under the EMBL-EBI Terms of Use available at https://www.ebi.ac.uk/about/terms-of-use. The BioSamples code is available at https://github.com/EBIBioSamples/biosamples-v4 and distributed under the Apache 2.0 license.

A compendium of uniformly processed human gene expression and splicing quantitative trait loci

Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue ( https://www.ebi.ac.uk/eqtl ), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

The European Nucleotide Archive in 2020

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena), provided by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), has for almost forty years continued in its mission to freely archive and present the world's public sequencing data for the benefit of the entire scientific community and for the acceleration of the global research effort. Here we highlight the major developments to ENA services and content in 2020, focussing in particular on the recently released updated ENA browser, modernisation of our release process and our data coordination collaborations with specific research communities.

Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics

Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.

The European Nucleotide Archive in 2019

The European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena) at the European Molecular Biology Laboratory's European Bioinformatics Institute provides open and freely available data deposition and access services across the spectrum of nucleotide sequence data types. Making the world's public sequencing datasets available to the scientific community, the ENA represents a globally comprehensive nucleotide sequence resource. Here, we outline ENA services and content in 2019 and provide an insight into selected key areas of development in this period.

BioSamples database: an updated sample metadata hub

The BioSamples database at EMBL-EBI provides a central hub for sample metadata storage and linkage to other EMBL-EBI resources. BioSamples has recently undergone major changes, both in terms of data content and supporting infrastructure. The data content has more than doubled from around 2 million samples in 2014 to just over 5 million samples in 2018. Fast, reciprocal data exchange was fully established between sister Biosample databases and other INSDC partners, enabling a worldwide common representation and centralization of sample metadata. The BioSamples platform has been upgraded to accommodate anticipated increases in the number of submissions via GA4GH driver projects such as the Human Cell Atlas and the EGA, as well as from mirroring of NCBI dbGaP data. The BioSamples database is now the authoritative repository for all INSDC sample metadata, an ELIXIR Deposition Database for Biomolecular Data and the EMBL-EBI sample metadata hub. To support faster turnaround for sample submission, and to increase scalability and resilience, we have upgraded the BioSamples database backend storage, APIs and user interface. Finally, the website has been redesigned to allow search and retrieval of records based on specific filters, such as ‘disease’ or ‘organism’. These changes are targeted at answering current use cases as well as providing functionalities for future emerging and anticipated developments. Availability: The BioSamples database is freely available at http://www.ebi.ac.uk/biosamples. Content is distributed under the EMBL-EBI Terms of Use available at https://www.ebi.ac.uk/about/terms-of-use.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019

The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 10⁹ individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog

The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

Rapid establishment of the European Bank for induced Pluripotent Stem Cells (EBiSC) - the Hot Start experience

A fast track "Hot Start" process was implemented to launch the European Bank for Induced Pluripotent Stem Cells (EBiSC) to provide early release of a range of established control and disease linked human induced pluripotent stem cell (hiPSC) lines. Established practice amongst consortium members was surveyed to arrive at harmonised and publically accessible Standard Operations Procedures (SOPs) for tissue procurement, bio-sample tracking, iPSC expansion, cryopreservation, qualification and distribution to the research community. These were implemented to create a quality managed foundational collection of lines and associated data made available for distribution. Here we report on the successful outcome of this experience and work flow for banking and facilitating access to an otherwise disparate European resource, with lessons to benefit the international research community. ETOC: The report focuses on the EBiSC experience of rapidly establishing an operational capacity to procure, bank and distribute a foundational collection of established hiPSC lines. It validates the feasibility and defines the challenges of harnessing and integrating the capability and productivity of centres across Europe using commonly available resources currently in the field.

The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)

The NHGRI-EBI GWAS Catalog has provided data from published genome-wide association studies since 2008. In 2015, the database was redesigned and relocated to EMBL-EBI. The new infrastructure includes a new graphical user interface (www.ebi.ac.uk/gwas/), ontology supported search functionality and an improved curation interface. These developments have improved the data release frequency by increasing automation of curation and providing scaling improvements. The range of available Catalog data has also been extended with structured ancestry and recruitment information added for all studies. The infrastructure improvements also support scaling for larger arrays, exome and sequencing studies, allowing the Catalog to adapt to the needs of evolving study design, genotyping technologies and user needs in the future.

Open Targets: a platform for therapeutic target identification and validation

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.

PhenoImageShare: an image annotation and query infrastructure

Background

High throughput imaging is now available to many groups and it is possible to generate a large quantity of high quality images quickly. Managing this data, consistently annotating it, or making it available to the community are all challenges that come with these methods.

Results

PhenoImageShare provides an ontology-enabled lightweight image data query, annotation service and a single point of access backed by a Solr server for programmatic access to an integrated image collection enabling improved community access. PhenoImageShare also provides an easy to use online image annotation tool with functionality to draw regions of interest on images and to annotate them with terms from an autosuggest-enabled ontology-lookup widget. The provenance of each image, and annotation, is kept and links to original resources are provided. The semantic and intuitive search interface is species and imaging technology neutral. PhenoImageShare now provides access to annotation for over 100,000 images for 2 species.

Conclusion

The PhenoImageShare platform provides underlying infrastructure for both programmatic access and user-facing tools for biologists enabling the query and annotation of federated images. PhenoImageShare is accessible online at http://www.phenoimageshare.org.

The cellular microscopy phenotype ontology

Background

Phenotypic data derived from high content screening is currently annotated using free-text, thus preventing the integration of independent datasets, including those generated in different biological domains, such as cell lines, mouse and human tissues.

Description

We present the Cellular Microscopy Phenotype Ontology (CMPO), a species neutral ontology for describing phenotypic observations relating to the whole cell, cellular components, cellular processes and cell populations. CMPO is compatible with related ontology efforts, allowing for future cross-species integration of phenotypic data. CMPO was developed following a curator-driven approach where phenotype data were annotated by expert biologists following the Entity-Quality (EQ) pattern. These EQs were subsequently transformed into new CMPO terms following an established post composition process.

Conclusion

CMPO is currently being utilized to annotate phenotypes associated with high content screening datasets stored in several image repositories including the Image Data Repository (IDR), MitoSys project database and the Cellular Phenotype Database to facilitate data browsing and discoverability.

Webulous and the Webulous Google Add-On--a web service and application for ontology building from templates

BACKGROUND

Authoring bio-ontologies is a task that has traditionally been undertaken by skilled experts trained in understanding complex languages such as the Web Ontology Language (OWL), in tools designed for such experts. As requests for new terms are made, the need for expert ontologists represents a bottleneck in the development process. Furthermore, the ability to rigorously enforce ontology design patterns in large, collaboratively developed ontologies is difficult with existing ontology authoring software.

DESCRIPTION

We present Webulous, an application suite for supporting ontology creation by design patterns. Webulous provides infrastructure to specify templates for populating ontology design patterns that get transformed into OWL assertions in a target ontology. Webulous provides programmatic access to the template server and a client application has been developed for Google Sheets that allows templates to be loaded, populated and resubmitted to the Webulous server for processing.

CONCLUSIONS

The development and delivery of ontologies to the community requires software support that goes beyond the ontology editor. Building ontologies by design patterns and providing simple mechanisms for the addition of new content helps reduce the overall cost and effort required to develop an ontology. The Webulous system provides support for this process and is used as part of the development of several ontologies at the European Bioinformatics Institute.

Expression Atlas update--an integrated database of gene and protein expression in humans, animals and plants

Expression Atlas (http://www.ebi.ac.uk/gxa) provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons-estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: 'enrichment' in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.

ArrayExpress update--simplifying data submissions

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is an international functional genomics database at the European Bioinformatics Institute (EMBL-EBI) recommended by most journals as a repository for data supporting peer-reviewed publications. It contains data from over 7000 public sequencing and 42 000 array-based studies comprising over 1.5 million assays in total. The proportion of sequencing-based submissions has grown significantly over the last few years and has doubled in the last 18 months, whilst the rate of microarray submissions is growing slightly. All data in ArrayExpress are available in the MAGE-TAB format, which allows robust linking to data analysis and visualization tools and standardized analysis. The main development over the last two years has been the release of a new data submission tool Annotare, which has reduced the average submission time almost 3-fold. In the near future, Annotare will become the only submission route into ArrayExpress, alongside MAGE-TAB format-based pipelines. ArrayExpress is a stable and highly accessed resource. Our future tasks include automation of data flows and further integration with other EMBL-EBI resources for the representation of multi-omics data.

The NHGRI GWAS Catalog, a curated resource of SNP-trait associations

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 × 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.

The NHGRI GWAS Catalog, a curated resource of SNP-trait associations

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 × 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.

Expression Atlas update--a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of 'baseline' expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful 'contrasts', i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user.

Updates to BioSamples database at European Bioinformatics Institute

The BioSamples database at the EBI (http://www.ebi.ac.uk/biosamples) provides an integration point for BioSamples information between technology specific databases at the EBI, projects such as ENCODE and reference collections such as cell lines. The database delivers a unified query interface and API to query sample information across EBI's databases and provides links back to assay databases. Sample groups are used to manage related samples, e.g. those from an experimental submission, or a single reference collection. Infrastructural improvements include a new user interface with ontological and key word queries, a new query API, a new data submission API, complete RDF data download and a supporting SPARQL endpoint, accessioning at the point of submission to the European Nucleotide Archive and European Genotype Phenotype Archives and improved query response times.

ArrayExpress update--trends in database growth and links to data analysis tools

The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is one of three international functional genomics public data repositories, alongside the Gene Expression Omnibus at NCBI and the DDBJ Omics Archive, supporting peer-reviewed publications. It accepts data generated by sequencing or array-based technologies and currently contains data from almost a million assays, from over 30 000 experiments. The proportion of sequencing-based submissions has grown significantly over the last 2 years and has reached, in 2012, 15% of all new data. All data are available from ArrayExpress in MAGE-TAB format, which allows robust linking to data analysis and visualization tools, including Bioconductor and GenomeSpace. Additionally, R objects, for microarray data, and binary alignment format files, for sequencing data, have been generated for a significant proportion of ArrayExpress data.

MageComet--web application for harmonizing existing large-scale experiment descriptions

Motivation: Meta-analysis of large gene expression datasets obtained from public repositories requires consistently annotated data. Curation of such experiments, however, is an expert activity which involves repetitive manipulation of text. Existing tools for automated curation are few, which bottleneck the analysis pipeline.

Results: We present MageComet, a web application for biologists and annotators that facilitates the re-annotation of gene expression experiments in MAGE-TAB format. It incorporates data mining, automatic annotation, use of ontologies and data validation to improve the consistency and quality of experimental meta-data from the ArrayExpress Repository.

Availability and implementation: Source and tutorials for MageComet are openly available at goo.gl/8LQPR under the GNU GPL v3 licenses. An implementation can be found at goo.gl/IdCuA

Contact:parkinson@ebi.ac.uk or xue.vin@gmail.com

Gene Expression Atlas update--a value-added database of microarray and sequencing-based functional genomics experiments

Gene Expression Atlas (http://www.ebi.ac.uk/gxa) is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions. The content of this database derives from curation, re-annotation and statistical analysis of selected data from the ArrayExpress Archive and the European Nucleotide Archive. A simple interface allows the user to query for differential gene expression either by gene names or attributes or by biological conditions, e.g. diseases, organism parts or cell types. Since our previous report we made 20 monthly releases and, as of Release 11.08 (August 2011), the database supports 19 species, which contains expression data measured for 19 014 biological conditions in 136 551 assays from 5598 independent studies.

Anatomy ontologies and potential users: bridging the gap

Motivation

To evaluate how well current anatomical ontologies fit the way real-world users apply anatomy terms in their data annotations.

Methods

Annotations from three diverse multi-species public-domain datasets provided a set of use cases for matching anatomical terms in two major anatomical ontologies (the Foundational Model of Anatomy and Uberon), using two lexical-matching applications (Zooma and Ontology Mapper).

Results

Approximately 1500 terms were identified; Uberon/Zooma mappings provided 286 matches, compared to the control and Ontology Mapper returned 319 matches. For the Foundational Model of Anatomy, Zooma returned 312 matches, and Ontology Mapper returned 397.

Conclusions

Our results indicate that for our datasets the anatomical entities or concepts are embedded in user-generated complex terms, and while lexical mapping works, anatomy ontologies do not provide the majority of terms users supply when annotating data. Provision of searchable cross-products for compositional terms is a key requirement for using ontologies.

OntoCAT--simple ontology search and integration in Java, R and REST/JavaScript

Background

Ontologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are now available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal. However, these resources differ substantially in mode, ease of access, and ontology content. This makes it relatively difficult to access each ontology source separately, map their contents to research data, and much of this effort is being replicated across different research groups.

Results

OntoCAT provides a seamless programming interface to query heterogeneous ontology resources including OLS and BioPortal, as well as user-specified local OWL and OBO files. Each resource is wrapped behind easy to learn Java, Bioconductor/R and REST web service commands enabling reuse and integration of ontology software efforts despite variation in technologies. It is also available as a stand-alone MOLGENIS database and a Google App Engine application.

Conclusions

OntoCAT provides a robust, configurable solution for accessing ontology terms specified locally and from remote services, is available as a stand-alone tool and has been tested thoroughly in the ArrayExpress, MOLGENIS, EFO and Gen2Phen phenotype use cases.

Availability

http://www.ontocat.org

ArrayExpress update--an archive of microarray and high-throughput sequencing-based functional genomics experiments

The ArrayExpress Archive (http://www.ebi.ac.uk/arrayexpress) is one of the three international public repositories of functional genomics data supporting publications. It includes data generated by sequencing or array-based technologies. Data are submitted by users and imported directly from the NCBI Gene Expression Omnibus. The ArrayExpress Archive is closely integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Advanced queries provided via ontology enabled interfaces include queries based on technology and sample attributes such as disease, cell types and anatomy.

Annotare--a tool for annotating high-throughput biomedical investigations and resulting data

Summary: Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a standards-compliant way that facilitates meaningful search and analysis.

Availability and Implementation: Annotare is available from http://code.google.com/p/annotare/ under the terms of the open-source MIT License (http://www.opensource.org/licenses/mit-license.php). It has been tested on both Mac and Windows.

Contact:rshankar@stanford.edu

ArrayExpress update--from an archive of functional genomics experiments to the atlas of gene expression

ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository--a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse--a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas--a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200,000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently-ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.