diff --git a/_data/tool_and_resource_list.yml b/_data/tool_and_resource_list.yml index b32693a1f..8dcb783b4 100755 --- a/_data/tool_and_resource_list.yml +++ b/_data/tool_and_resource_list.yml @@ -2265,12 +2265,12 @@ fairsharing: f5zx00 tess: Expression Atlas url: https://www.ebi.ac.uk/gxa/home -- description: Accessible database designed by scientist for scientist, to improve the sharing of influenza data. +- description: A web-based platform for sharing viral sequence data, initially for influenza data, and now for other pathogens (including SARS-CoV-2). id: gisaid - name: GISAID + name: Global Initiative on Sharing All Influenza Data (GISAID) registry: - fairsharing: ba6a09 - url: https://www.gisaid.org + fairsharing: 2f7f9f + url: https://gisaid.org - description: Protein Data Bank in Europe Knowledge Base id: pdbe-kb name: PDBe-KB @@ -2660,3 +2660,57 @@ id: better-bibtex name: Better BibTeX (BBT) url: https://retorque.re/zotero-better-bibtex/ +- description: GA4GH frames policy and builds standards to meet the real-world needs of the global genomics and health community. + id: ga4gh + name: Global Alliance for Genomics and Health (GA4GH) + url: https://www.ga4gh.org + registry: + biotools: ga4gh + fairsharing: 2tpx4v + tess: GA4GH +- description: Discover tools and best practices for working with infectious disease data. IDTk provides general guidance as well as specific information for pathogen characterisation, socioeconomic data, human biomolecular data, and human clinical and health data. + id: idtk + name: Infectious Diseases Toolkit (IDTk) + url: https://www.infectious-diseases-toolkit.org/ +- description: The Beyond 1 Million Genomes (B1MG) project is helping to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. + id: beyond-1-million-genomes + name: Beyond 1 Million Genomes (B1MG) + url: https://b1mg-project.eu/ +- description: The Federated EGA is an infrastructure built upon the European Genome-phenome Archive (EGA), an EMBL-EBI and CRG data resource for secure archiving and sharing of human sensitive biomolecular and phenotypic data resulting from biomedical research projects. + id: fega + name: Federated EGA + registry: + tess: Federated EGA + url: https://ega-archive.org/about/projects-and-funders/federated-ega/ +- description: The Pathogens Portal aims to provide access to data and tools relating to pathogens, their human and animal hosts and their vectors. Current content spans bacterial, viral and eukaryotic parasite lineages alongside human host data. + id: pathogens-portal + name: Pathogens Portal + registry: + fairsharing: a085b2 + tess: Pathogens Portal + url: https://www.pathogensportal.org/ +- description: NCBI Pathogen Detection integrates bacterial and fungal pathogen genomic sequences from numerous ongoing surveillance and research efforts whose sources include food, environmental sources such as water or production facilities, and patient samples. Foodborne, hospital-acquired, and other clinically infectious pathogens are included. + id: pathogen-detection + name: Pathogen Detection + url: https://www.ncbi.nlm.nih.gov/pathogens/ +- description: The COVID-19 Data Portal enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets. The aim of the COVID-19 Data Portal is to facilitate data sharing and analysis, and to accelerate coronavirus research. The portal includes relevant datasets submitted to EMBL-EBI as well as other major centres for biomedical data. The COVID-19 Data Portal is the primary entry point into the functions of a wider project, the European COVID-19 Data Platform. + id: covid-19-data-portal + name: COVID-19 Data Portal + registry: + biotools: covid-19-data-portal + fairsharing: f3b7a9 + tess: COVID-19 Data Portal + url: https://www.covid19dataportal.org/ +- description: The Disease Ontology has been developed as a standardised ontology for human disease to provide the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics, underlying mechanisms and related medical vocabulary disease concepts. + name: Disease Ontology (DOID) + id: doid + url: http://www.disease-ontology.org + registry: + fairsharing: 8b6wfq +- description: The Genomic Epidemiology Ontology (GenEpiO) covers vocabulary necessary to identify, document and research food-borne pathogens, infectious disease surveillance and outbreak investigations. + name: Genomic Epidemiology Ontology (GenEpiO) + id: genepio + url: https://genepio.org/ + registry: + fairsharing: y1mmbv + diff --git a/pages/your_domain/human_pathogen_genomics.md b/pages/your_domain/human_pathogen_genomics.md index 09caa84a7..f682748f5 100644 --- a/pages/your_domain/human_pathogen_genomics.md +++ b/pages/your_domain/human_pathogen_genomics.md @@ -18,14 +18,14 @@ related_pages: ## Introduction The human pathogen genomics domain focuses on studying the genetic code of organisms that cause disease in humans. Studies to identify and understand pathogens are conducted across different types of organisations ranging from research institutes to regional public health authorities. The aims can include urgent outbreak response, prevention measures, and developing remedies such as treatments and vaccines. -Data management challenges in this domain include the potential urgency of data sharing and secondary use of data across initiatives emerging from research, public health and policy. While the pathogenic organisms are the object of interest, there are many considerations to account for when dealing with samples collected from patients, pathogen surveillance, and human research subjects. +Data management challenges in this domain include the potential urgency of data sharing and secondary use of data across initiatives emerging from research, public health and policy. While the pathogenic organisms are the object of interest, there are many considerations to take into account when dealing with samples collected from patients, pathogen surveillance, and human research subjects. -The genomic data can represent anything from the genetic sequence of a single pathogen isolate to various fragments of genetic materials from a flora of pathogens in larger population. Other data can represent a wide range of contextual information about the human host, the disease, and various environmental factors. +The genomic data can represent anything from the genetic sequence of a single pathogen isolate to various fragments of genetic materials from a flora of pathogens in a larger population. Other data can represent a wide range of contextual information about the human host, the disease, and various environmental factors. ## Planning a study with pathogen genomic data ### Description -While the object of interest in this domain are pathogens, the data is usually derived from samples originating from patients and human research subjects. This means that you must plan to either remove or to handle [human data](human_data) during your study. +While the objects of interest in this domain are pathogens, the data is usually derived from samples originating from patients and human research subjects. This means that you must plan to either remove or handle [human data](human_data) during your study. ### Considerations @@ -35,12 +35,12 @@ While the object of interest in this domain are pathogens, the data is usually d * What is the appropriate scope for the legal and ethical agreements necessary for the study? * How should statements related to data processing be phrased to allow timely and efficient data sharing? * How much time would be required to negotiate access to the samples and data for the study? -* What public health and research initives should you consider aligning with? +* What public health and research initiatives should you consider aligning with? * What data could be shared with or reused from other initiatives during the project? * How will you align your practices with these initiatives to maximise the impact of the data and insight generated by the project? * How will you share data with your collaborators and other initiatives? * What conventions will you adopt when planning your study? - * What existing protocols should you consider adopting for sample preparation, sequencing, variant calling etc? + * What existing protocols should you consider adopting for operations such as sample preparation, sequencing, and variant calling? * What conventions should you adopt for documenting your research? ### Solutions @@ -51,10 +51,10 @@ While the object of interest in this domain are pathogens, the data is usually d * [Processing and analysing human data](human_data#processing-and-analysing-human-data) #### Isolate pathogen from host information -* Depending on the pathogen, how it interacts with the host, or the methods applied, it can be possible to generate clean isolates that do not contain host related material. Data produced from a clean isolate could potentially be handled with few restrictions, while other data will be considered to be personal and [sensitive](data_sensitivity) that need [protection](data_security). +* Depending on the pathogen and how it interacts with the host or the methods applied, it can be possible to generate clean isolates that do not contain host-related material. Data produced from a clean isolate could potentially be handled with few restrictions, while other data will be considered to be personal and [sensitive](data_sensitivity) and will need [protection](data_security). #### Public health initiatives -* National and international recommendations from public health authorities, epidemic surveillance programs and research data communities should be considered when planning a new study or surveillance programme. In particular, you could consult conventions for relevant surveillance programs while considering widely adopted guidelines for research documentation, and instructions from the data sharing platforms. +* National and international recommendations from public health authorities, epidemic surveillance programs and research data communities should be considered when planning a new study or surveillance programme. In particular, you could consult conventions for relevant surveillance programs while considering widely adopted guidelines for research documentation, and instructions from the data-sharing platforms. * [European Centre for Disease Prevention and Control (ECDC)](https://www.ecdc.europa.eu/en) coordinates [Disease and laboratory networks](https://www.ecdc.europa.eu/en/about-ecdc/what-we-do/partners-and-networks/disease-and-laboratory-networks) and also issues [Surveillance and reporting protocols](https://www.ecdc.europa.eu/en/search?s=protocol) and other [Technical guidance on sequencing](https://www.ecdc.europa.eu/en/search?s=protocol). * [WHO genomic surveillance strategy](https://www.who.int/initiatives/genomic-surveillance-strategy) and [guidance on implementation for maximum impact on public health](https://apps.who.int/iris/handle/10665/338480) and there are published reports that advise on [Implementing Quality Management Systems in Public Health Laboratories](https://doi.org/10.1128/jcm.00261-19). * The US Centers for Disease Control and Prevention (CDC) offers guidance on [Pathogen genomics](https://www.cdc.gov/genomics/pathogen/index.htm) for its work in monitoring, investigating, and controlling infectious diseases. @@ -62,13 +62,13 @@ While the object of interest in this domain are pathogens, the data is usually d #### Sequencing experiments * Good practices for genome experiments suggest that the documentation, at a minimum, should describe the design of the study or surveillance program, the collected specimens and how the samples were prepared, the experimental setup and protocols, and the analysis workflow. - * Adopt recommendations specifically for genomics and pathogen genomics such as [Ten simple rules for annotating sequencing experiments](https://doi.org/10.1371/journal.pcbi.1008260). - * Refer to general guidance on how to provide [documentation and metadata](metadata_management) during your project. + * Adopt specific genomics and pathogen genomics recommendations such as [Ten simple rules for annotating sequencing experiments](https://doi.org/10.1371/journal.pcbi.1008260). + * Refer to the general guidance on providing [documentation and metadata](metadata_management) during your project. * Adopt standards, conventions and robust protocols to maximise the reuse potential of the data in parallel initiatives and your future projects. - * The Genomic Standards Consortium (GSC) develops and maintains the [GSC Minimum Information about any Sequence (MIxS)](https://fairsharing.org/FAIRsharing.9aa0zp) set of core and extended descriptors for genomes and metagenomes with associated samples and their environment to guide scientists on how to capture the metadata essential for high quality research. - * The GenEpiO Consortium develops and maintains the [Genomic Epidemiology Application Ontology (GenEpiO)](https://doi.org/10.25504/FAIRsharing.y1mmbv) to support data sharing and integration specifically for foodborne infectious disease surveillance and outbreak investigations. + * The Genomic Standards Consortium (GSC) develops and maintains the {% tool "mixs" %} and the {% tool "migs-mims" %}set of core and extended descriptors for genomes and metagenomes with associated samples and their environment to guide scientists on how to capture the metadata essential for high-quality research. + * The GenEpiO Consortium develops and maintains the {% tool "genepio" %} to support data sharing and integration specifically for foodborne infectious disease surveillance and outbreak investigations. * The [Public Health Alliance for Genomic Epidemiology (PHA4GE)](https://pha4ge.org/) supports openness and interoperability in public health bioinformatics. The [Data Structures working group](https://pha4ge.org/working-groups/) develops, adapts and standardises data models for microbial sequence data, contextual metadata, results and workflow metrics, such as the [SARS-CoV-2 contextual data specification](https://github.com/pha4ge/SARS-CoV-2-Contextual-Data-Specification). - * ISO (the International Organization for Standardization) has issued standards that can be referenced when designing or commissioning genomic sequencing and informatics services, such as + * The International Organization for Standardization (ISO) has issued standards that can be referenced when designing or commissioning genomic sequencing and informatics services, such as * [ISO 20397-1:2022 Biotechnology — Massively parallel sequencing — Part 1: Nucleic acid and library preparation](https://www.iso.org/standard/74054.html) * [ISO 20397-2:2021 Biotechnology — Massively parallel sequencing — Part 2: Quality evaluation of sequencing data](https://www.iso.org/standard/67895.html) * [ISO/TS 20428:2017 Health informatics — Data elements and their metadata for describing structured clinical genomic sequence information in electronic health records](https://www.iso.org/standard/67981.html) @@ -84,8 +84,8 @@ While the object of interest in this domain are pathogens, the data is usually d * How will you capture information about the configuration and quality of the sequencing results? * How will you ensure that the information captured is complete and correct? * What data and file formats should you consider for your project? - * What are the *de-facto* standards used for the experiment type and down-stream analysis-pipelines? - * Where are the instrument specific aspects for the data and files formats documented? + * What are the *de-facto* standards used for the experiment type and downstream analysis pipelines? + * Where are the instrument-specific aspects of the data and file formats documented? * What existing data will you integrate or use as a reference in your project? * What reference genome(s) will you need access to? * What is the recommended citation for the data and their versions? @@ -94,57 +94,57 @@ While the object of interest in this domain are pathogens, the data is usually d #### Filtering genomic reads corresponding to human DNA fragments -* Data files with reads produced by sequencing experiments sometimes contain fragments of the host organism’s DNA. When the host is a human research subject or patient, these fragments can be masked or removed to produce files that could potentially be handled with fewer restrictions. The approach chosen to mask the host associated reads leads to different trade-offs. Make sure to include this as a factor in your risk assessment. - * Mapping to (human) host reference genomes, [can inadvertently leave some host associated reads unmasked](https://doi.org/10.1099%2Fmgen.0.000393). - * Mapping to pathogens reference genomes can inadvertently mask some pathogen associated reads and still leave some host associated reads unmasked +* Data files with reads produced by sequencing experiments sometimes contain fragments of the host organism’s DNA. When the host is a human research subject or patient, these fragments can be masked or removed to produce files that could potentially be handled with fewer restrictions. The approach chosen to mask the host-associated reads leads to different trade-offs. Make sure to include this as a factor in your risk assessment. + * Mapping to (human) host reference genomes, [can inadvertently leave some host-associated reads unmasked](https://doi.org/10.1099%2Fmgen.0.000393). + * Mapping to pathogens reference genomes can inadvertently mask some pathogen-associated reads and still leave some host-associated reads unmasked * [Removal of human reads from SARS-CoV-2 sequencing data \| Galaxy training](https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/human-reads-removal/tutorial.html) #### Contextual information about the sample -* Information about the host phenotype, context and disease is often necessary to answer questions in a research study or policy perspective. Other contextual information can include non-host related environmental factors, such as interactions with other pathogens, drugs and geographic proliferation. It can also include information about the sampled material and how it was processed for sequencing. +* Information about the host phenotype, context and disease is often necessary to answer questions in a research study or policy perspective. Other contextual information can include non-host-related environmental factors, such as interactions with other pathogens, drugs and geographic proliferation. It can also include information about the sampled material and how it was processed for sequencing. * Adopt common reporting checklists, data dictionaries, terms and vocabularies to simplify data sharing across initiatives. - * ENA hosts a selection of [sample checklists](https://www.ebi.ac.uk/ena/browser/checklists) that can be used to annotate sequencing experiements, including checklists derived from the [MIxS consortium](http://w3id.org/mixs). The [ENA virus pathogen reporting standard checklist](https://www.ebi.ac.uk/ena/browser/view/ERC000033) has been widely used for SARS-CoV-2 genomic studies. - * Reuse terms and definitions from existing vocabularies, such as the [Phenotypic QualiTy Ontology](https://www.ebi.ac.uk/ols4/ontologies/pato), [NCBI Taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy), [Disease Ontology](https://disease-ontology.org), [Chemical Entities of Biological Interest](https://bioportal.bioontology.org/ontologies/CHEBI/?p=summary), and [UBER anatomy ONtology](https://bioportal.bioontology.org/ontologies/UBERON). + * {% tool "european-nucleotide-archive" %} hosts a selection of [sample checklists](https://www.ebi.ac.uk/ena/browser/checklists) that can be used to annotate sequencing experiments, including checklists derived from {% tool "mixs" %}. The [ENA virus pathogen reporting standard checklist](https://www.ebi.ac.uk/ena/browser/view/ERC000033) has been widely used for SARS-CoV-2 genomic studies. + * Reuse terms and definitions from existing vocabularies, such as the [Phenotypic QualiTy Ontology](https://www.ebi.ac.uk/ols4/ontologies/pato), {% tool "ncbi-taxonomy" %}, {% tool "doid" %}, [Chemical Entities of Biological Interest](https://bioportal.bioontology.org/ontologies/CHEBI/?p=summary), and [UBER anatomy ONtology](https://bioportal.bioontology.org/ontologies/UBERON). * The [PHA4GE SARS-CoV-2 contextual data specification](https://github.com/pha4ge/SARS-CoV-2-Contextual-Data-Specification) is a comprehensive example including a reporting checklist, related protocols, and mappings to relevant vocabularies and data sharing platforms. #### Generating genomic data * Establish protocols and document the steps taken in the lab to process the sample and in the computational workflow to prepare the resulting data. Make sure to keep information from quality assurance procedures and strive to make your labwork and computational process as reproducible as possible. * [High-Throughput Sequencing \| LifeScienceRDMLookUp](https://elixir.no/rdm-lookup/sequencing) - * [The Beyond One Million Genomes (B1MG)](https://b1mg-project.eu) project provides guidelines that cover the minimum [quality requirements](https://zenodo.org/record/5018495) for the generation of genome sequencing data. + * {% tool"beyond-1-million-genomes" %} project provides guidelines that cover the minimum [quality requirements](https://zenodo.org/record/5018495) for the generation of genome sequencing data. * Data repositories generally have information about recommended [data file formats](data_publication) and [metadata](metadata_management) - * The [FAIR Cookbook](https://faircookbook.elixir-europe.org/content/home.html) provides instructions on [validation of file formats](https://faircookbook.elixir-europe.org/content/recipes/interoperability/fastq-file-format-validators.html) - * A good place to look for scientific and technical information about data quality validation software tools for pathogenomics is [Bio.Tools](https://bio.tools/t?page=1&q=validation&sort=score&topicID=%22topic_3168%22). - * The [Infectious Diseases Toolkit (IDTk)](https://www.infectious-diseases-toolkit.org/) has a showcase on [An automated SARS-CoV-2 genome surveillance system built around Galaxy](https://www.infectious-diseases-toolkit.org/showcase/covid19-galaxy) - * The Galaxy Training Network provides free on-line [training materials on quality control](https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/quality-control/tutorial.html). + * The {% tool "fair-cookbook" %} provides instructions on [validation of file formats](https://faircookbook.elixir-europe.org/content/recipes/interoperability/fastq-file-format-validators.html) + * A good place to look for scientific and technical information about data quality validation software tools for pathogenomics is [Bio.Tools](https://bio.tools/t?page=1&q=validation&sort=score&topicID=%22topic_3168%22). + * The {% tool "idtk" %} has a showcase on [An automated SARS-CoV-2 genome surveillance system built around Galaxy](https://www.infectious-diseases-toolkit.org/showcase/covid19-galaxy) + * The Galaxy Training Network provides free online [training materials on quality control](https://training.galaxyproject.org/training-material/topics/sequence-analysis/tutorials/quality-control/tutorial.html). ## Sharing and preserving pathogen genomic data ### Considerations -* What data need to be preserved by the project and for how long? +* What data needs to be preserved by the project and for how long? * What is preserved by others and how would someone find and access the data? * What databases should I use to share human pathogen genomics data? -* What other research information (such as protocols, computational tools, samples) can the project share? +* What other research information (such as protocols, computational tools, and samples) can the project share? ### Solutions -#### Sharing host related and other contextual information -* Some host related information can be personal and/or sensitive and care should be taken when storing and sharing it. Apply data masking and aggregation techniques to pseudonymise or anonymise the contextual information and take measures to separate personal and sensitive information from the pathogen data when possible. +#### Sharing host-related and other contextual information +* Some host-related information can be personal and/or sensitive and care should be taken when storing and sharing it. Apply data masking and aggregation techniques to pseudonymise or anonymise the contextual information and take measures to separate personal and sensitive information from the pathogen data when possible. * Adopt solutions for federated analysis to support distributed analyses on information that could otherwise not be shared, such as establishing contractual agreements with suitable regional or international data infrastructures. -* [GA4GH (Global Alliance for Genomics and Health)](https://www.ga4gh.org/what-we-do/) is a global organisation that frames policy and builds standards to meet the real-world needs of the genomics and health community. Its [GDPR & International Health Data Sharing Forum](https://www.ga4gh.org/product/gdpr-international-health-data-sharing-forum/) shares *GDPR Briefs* that represent a consensus position among its Forum Members (not legal advice) regarding the current understanding of the GDPR and its implications for genomic and health-related research, such as +* {% tool "ga4gh" %} is a global organisation that frames policy and builds standards to meet the real-world needs of the genomics and health community. Its [GDPR & International Health Data Sharing Forum](https://www.ga4gh.org/product/gdpr-international-health-data-sharing-forum/) shares *GDPR Briefs* that represent a consensus position among its Forum Members (not legal advice) regarding the current understanding of the GDPR and its implications for genomic and health-related research, such as * [GDPR Brief: data protection implications of publishing metadata to enable discovery](https://www.ga4gh.org/news_item/ga4gh-gdpr-brief-data-protection-implications-of-publishing-metadata-to-enable-discovery/) * [GDPR Brief: federated analysis for responsible data sharing under the GDPR](https://www.ga4gh.org/news_item/ga4gh-gdpr-brief-federated-analysis-for-responsible-data-sharing-under-the-gdpr/) #### Sharing pathogen genomic data * You should adopt good practices for [data sharing](sharing) and identify which data sharing platforms to use to reach the relevant stakeholders. You can use more than one platform but care should be taken to make sure that data is interconnected where possible to enable deduplication in downstream analyses. - * European healthcare surveillance systems is administered and used by public health authorities such as [ECDC’s TESSy/EpiPulse](https://www.ecdc.europa.eu/en/publications-data/epipulse-european-surveillance-portal-infectious-diseases) - * International research data exchanges such as [European Nucleotide Archive (ENA)](https://www.ebi.ac.uk/ena/browser/submit) for non-sensitive genomic data and the [Federated EGA](https://ega-archive.org/federated) network for sensitive data. - * There are also pathogen specifc initiatives, such as [EMBL-EBI Pathogens](https://www.ebi.ac.uk/ena/pathogens/home) and [NCBI Pathogen Detection](https://www.ncbi.nlm.nih.gov/pathogens/). And initiatives focusing specifically on viruses, certain pathogens or certain data types, such as [GISAID (Global Initiative on Sharing All Influenza Data)](https://gisaid.org/) for observations and assembled consensus sequences on a selection of pathogens. + * European healthcare surveillance systems are administered and used by public health authorities such as [ECDC’s TESSy/EpiPulse](https://www.ecdc.europa.eu/en/publications-data/epipulse-european-surveillance-portal-infectious-diseases) + * International research data exchanges such as {% tool "european-nucleotide-archive" %} for non-sensitive genomic data + * There are also pathogen specific initiatives, such as {% tool "pathogens-portal" %} and {% tool "pathogen-detection" %}. And initiatives focusing specifically on viruses, certain pathogens or certain data types, such as {% tool "gisaid"%} for observations and assembled consensus sequences on a selection of pathogens. * Investigate if there are [national resources](national_resources) or a [data brokering](data_brokering) organisation available to facilitate data sharing. - * [EBI Pathogens data hubs](https://www.ebi.ac.uk/ena/pathogens/v2/) - * [Submit new data \| European COVID-19 platform](https://www.covid19dataportal.org/submit-data) + * {% tool "pathogens-portal" %} Data Hubs network for sensitive data. + * {% tool "covid-19-data-portal" %}