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METAGENOTE

Synopsis

METAGENOTE (https://metagenote.niaid.nih.gov) is a project from the National Institutes of Health (NIH). The objective of this project is to streamline the submission process of biological samples and metadata to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) repository for public access. METAGENOTE compiles and manages the submission process on user’s behalf with an easy-to-use web interface. The platform offers a wide selection of templates for different types of biological and experimental studies with a special emphasis on the standardization of metadata reporting. Importantly, the standardization of metadata reporting permits consistent and reproducible downstream analysis across different studies. Metadata is documentation that describes data. Properly described and documented data allows the scientific community to understand and disseminate important details of the work. As sequencing projects become more commonplace, it is critically important that all biological samples should be made publicly available with standardized metadata reporting so that these samples can be reanalyzed to independently assess the veracity of the conclusions.

User Workflow

UserWorkflow

User Types

Registered Users

Registered users are able to store their work in METAGENOTE. Additionally, the registration form allows users to identify themselves as members of a particular lab. METAGENOTE offers the ability to view work being done by their peers. Currently, this feature is only available to NIH affiliated users.

SSO

METAGENOTE allows single-sign-on authentication to an IDP using SAML. Currently, METAGENOTE is configured to authenticate against NIH CIT.

Workspace

The METAGENOTE workspace is the primary work management area for registered users. The “My Workspace” page allows registered users to view the status and continue wok on previous sample groups, view sample groups previously submitted to SRA, and provides a read-only view to sample groups by lab member peers.

WIP

The Work-In-Progress (WIP) section of the workspace displays sample groups that have not been submitted to SRA. Sample groups in this section are labeled as one of three status – Incomplete, Publish, or Pending.

  • Incomplete - indicates that the sample group is missing data required by NCBI on at least one sample
  • Publish - when all required fields have been entered the status field of the sample group becomes a clickable button labeled Publish. This indicates the user’s samples are in a complete state ready to be accepted by SRA. The user may initiate the submission process by clicking the Publish button for the indicated sample group.
  • Pending – the submission process may potentially take several hours to be analyzed and processed by NCBI’s servers. While waiting for this processing to complete, the sample group is marked as Pending. This indicates that METAGENOTE is still waiting for a conclusive acceptance status from NCBI. Once the METAGENOTE system receives an indication that the users sample group has been posted as a public BioProject, the sample group is no longer considered as a work-in-progress and is marked as Published.
Published

The Published section in the My Workspace area lists sample groups accepted and published on SRA. The table listing these samples contains the SRA assigned BioProject Id along with a direct link to NCBI’s site with the published information for these annotations.

Lab

Lab sample groups are those that have been entered by members of the same lab. These sample annotations are displayed in a read-only and non-editable mode.

Non-Registered Users

Non-registered users submit their sample annotations directly to SRA without the storage and management features available to registered users.

Select Template

METAGENOTE provides a wizard style selection to guide users when choosing the appropriate BioSample Package for their samples. Selection is done in two general stages, select data source then package selection, to help the user target narrow and target the appropriate choice.

Templates

Template Descriptions

Metagenomics

Study of genetic material recovered directly from environmental samples

Survey (16S, 18S, ITS, other)

Sequences (e.g. 16S, 18S, 23S, 28S rRNA, ITS, COI) from samples obtained directly from the environment, without culturing or identification of the organisms. Example: 16S reads from mouse skin microbiome.

Metagenomes

Sequences obtained using whole genome sequencing on samples obtained directly from the environment, without culturing or identification of the organisms.

Specimen

Marker gene sequences obtained from any material identifiable by means of specimens.

  • Air Metagenomic survey of microbiome typically sampled from residential and hospital indoor ventilation system
  • Host Associated Metagenomic survey of microbiome with the emphasis on the ecological and physiological interactions between hosts and environment. Typical samples sources include skin or stool from mouse.
  • Human Associated Metagenomic survey of human associated microbiome sampled from the body sites such as anterior nares, retro auricular crease, saliva and nares
  • Human Gut Metagenomic survey of microbiome in human gastrointestinal track typically with samples from stool
  • Human Oral Metagenomic survey of oral microbiome sampled habitats such as teeth, gingival sulcus, tongue, cheeks, hard and soft palates, and tonsils
  • Human Skin Metagenomic survey of microbiome on human skin such as nare, external auditory canal, occiput, retroauricular crease, and volar forearm
  • Human Vaginal Metagenomic survey of vaginal microbiome sampled from locations such as poster fornix, mid vagina, and introitus
  • Microbial Metagenomic survey of microbiome without specific categories, such as ant fungus, beach sand, dust, fermentation, and compost
  • Miscellaneous Metagenomic survey of microbiome generally not classified in any particular categories, such as samples collected from debris after natural disaster and echinoderm
  • Plant Associated Metagenomic survey of microbiome in plants typically as a response to changes in environment with samples from, as an example, the roots
  • Sediment Metagenomic survey of microbiome sampled from the locations such as estuaries, wetland, and river bed
  • Soil Metagenomic survey of microbiome in soil sampled from the locations such forest, glaciers, and permafrost
  • Wastewater Metagenomic survey of microbiome typically sampled from sewage and sludge
  • Water Metagenomic survey of microbiome sampled from, for example, tap/drinking water, swimming pool, river, and ocean
Single microbial genomes

Study of complete DNA sequence of an organism's genome

Bacteria/Archaea Genome

Cultured bacterial/archaeal sample

Assembled genome

Metagenome assembled genome

Amplified genome

Single amplified genome

  • Air Single amplified genome typically sampled from residential and hospital indoor ventilation system
  • Host Associated Single amplified genome with the emphasis on the ecological and physiological interactions between hosts and environment. Typical samples sources include skin or stool from mouse.
  • Human Associated Single amplified genome from the body sites such as anterior nares, retro auricular crease, saliva and nares
  • Human Gut Single amplified genome in human gastrointestinal track typically with samples from stool
  • Human Oral Single amplified genome sampled habitats such as teeth, gingival sulcus, tongue, cheeks, hard and soft palates, and tonsils
  • Human Skin Single amplified genome on human skin such as nare, external auditory canal, occiput, retroauricular crease, and volar forearm
  • Human Vaginal Single amplified genome of vaginal microbiome sampled from locations such as poster fornix, mid vagina, and introitus
  • Microbial Single amplified genome without specific categories, such as ant fungus, beach sand, dust, fermentation, and compost
  • Miscellaneous Single amplified genome generally not classified in any particular categories, such as samples collected from debris after natural disaster and echinoderm
  • Plant Associated Single amplified genome in plants typically as a response to changes in environment with samples from, as an example, the roots
  • Sediment Single amplified genome sampled from the locations such as estuaries, wetland, and river bed
  • Soil Single amplified genome in soil sampled from the locations such forest, glaciers, and permafrost
  • Wastewater Single amplified genome typically sampled from sewage and sludge
  • Water Single amplified genome sampled from, for example, tap/drinking water, swimming pool, river, and ocean
Viral genome

Viral samples

  • Air Viral libraries typically sampled from residential and hospital indoor ventilation system
  • Host Associated Viral libraries with the emphasis on the ecological and physiological interactions between hosts and environment. Typical samples sources include skin or stool from mouse.
  • Human Associated Viral libraries sampled from the body sites such as anterior nares, retro auricular crease, saliva and nares
  • Human Gut Viral libraries in human gastrointestinal track typically with samples from stool
  • Human Oral Viral libraries sampled habitats such as teeth, gingival sulcus, tongue, cheeks, hard and soft palates, and tonsils
  • Human Skin Viral libraries on human skin such as nare, external auditory canal, occiput, retroauricular crease, and volar forearm
  • Human Vaginal Viral libraries sampled from locations such as poster fornix, mid vagina, and introitus
  • Microbial Viral libraries without specific categories, such as ant fungus, beach sand, dust, fermentation, and compost
  • Miscellaneous Viral libraries generally not classified in any particular categories, such as samples collected from debris after natural disaster and echinoderm
  • Plant Associated Viral libraries in plants typically as a response to changes in environment with samples from, as an example, the roots
  • Sediment Viral libraries sampled from the locations such as estuaries, wetland, and river bed
  • Soil Viral libraries in soil sampled from the locations such forest, glaciers, and permafrost
  • Wastewater Viral libraries typically sampled from sewage and sludge
  • Water Viral libraries sampled from, for example, tap/drinking water, swimming pool, river, and ocean
Uncultivated viral genome

Uncultivated viral genome

  • Air Uncultivated Virus Genome, Air; Version 5.0
  • Host Associated Uncultivated Virus Genome, Host-Associated; Version 5.0
  • Human Associated Uncultivated Virus Genome, Human-Associated; Version 5.0
  • Human Gut Uncultivated Virus Genome, Human-Gut; Version 5.0
  • Human Oral Uncultivated Virus Genome, Human-Oral; Version 5.0
  • Human Skin Uncultivated Virus Genome, Human-Skin; Version 5.0
  • Human Vaginal Uncultivated Virus Genome, Human-Vaginal; Version 5.0
  • Microbial Uncultivated Virus Genome, Microbial; Version 5.0
  • Miscellaneous Uncultivated Virus Genome, Miscellaneous; Version 5.0
  • Plant Associated Uncultivated Virus Genome, Plant-Associated; Version 5.0
  • Sediment Uncultivated Virus Genome, Sediment; Version 5.0
  • Soil Uncultivated Virus Genome, Soil; Version 5.0
  • Wastewater Uncultivated Virus Genome, Wastewater; Version 5.0
  • Water Uncultivated Virus Genome, Water; Version 5.0
Eukaryote/Model organism

Eukaryotic or multicellular samples

Model organism

Multicellular samples or cell lines derived from common laboratory model organisms, e.g., mouse, rat, Drosophila, worm, fish, frog, or large mammals including zoo and farm animals.

Eukaryote

Eukaryotic samples

Human-derived cell lines

For samples isolated from humans use the Pathogen, Microbe or appropriate MIxS package. Only use for human-derived cell line samples that have no privacy concerns.

Describe Samples: Sample Group Editor

The Sample Group editor provides a tool with a familiar "Excel-like" experience that allows users to efficiently annotate their samples.

  • Required Attributes - indicates sample atributes required by NCBI. These attributes must be filled to be accepted to the SRA.

  • Recommended Attributes - attributes recommended by METAGENOTE. While these values are not marked required by NCBI. These annotations are recommended by groups within the NIH.

  • Anatomy Tool - METAGENOTE features a graphical interface to aid users when annotating attributes requiring an anatomical location. Users indicate the site by clicking on a graphical depiction of the general anatomical area. METAGENOTE fills the attribute with a value from a standardized ontology value set such as the Foundational Model of Anatomy (FMA).

  • Ontology Lookup - context menus are available in the editor using a mouse right-click. A searchable set of ontology values may be used to help users quickly fill fields with standardized values.

  • Attribute Descriptions - every attribute in the editor is accompanied with a description to provide context, commonly used values, and expected formatting of input.

  • Export - the sample group editor allows users to export their work locally to their comoputer as an Excel formatted file

  • Import - METAGENOTE features an import tool for existing sample annotations. The import may be CSV formatted or an Excel binary file. The import process will automatically map column headers to the selected package

Submit to SRA

When users have completed furnishing their sample metadata. The final step is the SRA submission process. This process generates the formatted XML files SRA requires and transfers the sample group data to their servers.

Upload Sequence Files

SRA requires the sample metadata be accompanied with their raw sequence files. Accepted formats are FASTQ, SFF, BAM, and HDF5. More information may be found at SRA's file format page.

Map Samples to Sequence Files

METAGENOTE will attempt to group and assign the uploaded sequence files to samples. Groupings, such as forward and reverse reads, is established using similarities and common filename conventions. Additionally, METAGENOTE will determine if assignments may be established when sample names are embedded in the sequence filenames.

Describe Project

SRA requires a general project description for representation as a BioProject.

Project Name - The title for public display

Project Title - A paragraph description of the study goals and relevance

Sequencing Platform

  • _LS454
  • ABI_SOLID
  • BGISEQ
  • CAPILLARY
  • COMPLETE_GENOMIC
  • HELICOS
  • ILLUMINA
  • ION_TORRENT
  • OXFORD_NANOPORE

Sequencing Instrument

The choice of sequencing instrument is dependent on the Sequencing Platform specified.

  • _LS454
    • 454 GS
    • 454 GS 20
    • 454 GS FLX
    • 454 GS FLX+
    • 454 GS FLX Titanium
    • 454 GS Junior
  • ABI_SOLID
    • AB 5500 Genetic Analyzer
    • AB 5500xl Genetic Analyzer
    • AB 5500x-Wl Genetic Analyzer
    • AB SOLiD 3 Plus System
    • AB SOLiD 4 System
    • AB SOLiD 4hq System
    • AB SOLiD PI System
    • AB SOLiD System
    • AB SOLiD System 2.0
    • AB SOLiD System 3.0
  • BGISEQ
    • BGISEQ-500
  • CAPILLARY
    • AB 310 Genetic Analyzer
    • AB 3130 Genetic Analyzer
    • AB 3130xL Genetic Analyzer
    • AB 3500 Genetic Analyzer
    • AB 3500xL Genetic Analyzer
    • AB 3730 Genetic Analyzer
    • AB 3730xL Genetic Analyzer
  • COMPLETE_GENOMIC
    • Complete Genomics
  • HELICOS
    • Helicos HeliScope
  • ILLUMINA
    • HiSeq X Five
    • HiSeq X Ten
    • Illumina Genome Analyzer
    • Illumina Genome Analyzer II Illumina Genome Analyzer IIx
    • Illumina HiScanSQ
    • Illumina HiSeq 1000
    • Illumina HiSeq 1500
    • Illumina HiSeq 2000
    • Illumina HiSeq 2500
    • Illumina HiSeq 3000
    • Illumina HiSeq 4000
    • Illumina iSeq 100
    • Illumina NovaSeq 6000
    • Illumina MiniSeq
    • Illumina MiSeq
    • NextSeq 500
    • NextSeq 550
  • ION_TORRENT
    • Ion Torrent PGM
    • Ion Torrent Proton
    • Ion Torrent S5 XL
    • Ion Torrent S5
  • OXFORD_NANOPORE
    • GridION
    • MinION
    • PromethION
    • PACBIO_SMRT
    • PacBio RS
    • PacBio RS II
    • PacBio Sequel

Read Orientation

  • Forward
  • Reverse

Library Strategy

  • AMPLICON
  • ATAC-seq
  • Bisulfite-Seq
  • ChIA-PET
  • ChIP-Seq
  • CLONE
  • CLONEEND
  • CTS
  • DNase-Hypersensitivity
  • EST
  • FAIRE-seq
  • FINISHING
  • FL-cDNA
  • Hi-C
  • MBD-Seq
  • MeDIP-Seq
  • miRNA-Seq
  • MNase-Seq
  • MRE-Seq
  • ncRNA-Seq
  • OTHER
  • POOLCLONE
  • RAD-Seq
  • RIP-Seq
  • RNA-Seq
  • SELEX
  • ssRNA-seq
  • Synthetic-Long-Read
  • Targeted-Capture
  • Tethered Chromatin Conformation Capture
  • Tn-Seq
  • WCS
  • WGA
  • WGS
  • WXS

Data Type

  • Assembly
  • Clone Ends
  • Epigenomics
  • Exome
  • Genome Sequencing
  • Genotype
  • MAP
  • Metagenome
  • Metagenomic Assembly
  • Other
  • Phenotype
  • Proteomic
  • Random Survey
  • Targeted Loci
  • Transcriptome
  • Variation

Library Source

  • Genomic Single Cell
  • Genomic
  • Metagenomic
  • Metatranscriptomic
  • Other
  • Synthetic
  • Transcriptomic Single Cell
  • Transcriptomic
  • Viral RNA

Library Selection

  • 5-methylcytidine antibody
  • CAGE
  • cDNA
  • cDNA_oligo_dT
  • cDNA_randomPriming
  • CF-H
  • CF-M
  • CF-S
  • CF-T
  • ChIP
  • DNAse
  • HMPR
  • Hybrid Selection
  • Inverse rRNA
  • MBD2 protein methyl-CpG binding domain
  • MDA
  • MF
  • MNase
  • MSLL
  • Oligo-dT
  • other
  • Padlock probes capture method
  • PCR
  • PolyA
  • RACE
  • RANDOM
  • RANDOM PCR
  • Reduced Representation
  • repeat fractionation
  • Restriction Digest
  • RT-PCR
  • size fractionation
  • unspecified

Description

Relevant information about the submission, such as the summary of the project and experiments, title and abstract of the published manuscript, contact person(s), and/or name(s) of the principal investigator(s). As an example: Alterations in the intestinal microbiome and loss of mucosal integrity contribute to inflammation during HIV disease. The intestinal microbiome was analyzed among 12 participants. Intestinal microbiota diversity, phyla and family abundance demonstrated stability after rh-lactoferrin or placebo treatment. See PRJNA513489 for additional details.

Corresponding Email - the user's contact email

Contact Person or PI

Hold Release Date - set a public release date for SRA

Metadata Standardization in METAGENOTE

The SRA promises great biological insight if metadata can be analyzed in aggregate. However, the metadata submitted to the SRA remain underutilized because of the poor structure of the data associated with each sample. The SRA generally does not enforce a standardized set of terms that should be used to describe the biological samples. As a consequence, the metadata include many synonyms, spelling variants and references to outside sources of information. It has been difficult to perform large-scale analyses that identify the relationships between molecular processes and phenotype across diverse diseases, tissues and cell types present in the SRA. A major component of biological metadata is the sample attributes. Sample attributes define the material under investigation and can include sample characteristics such as cell type, collection site and phenotypic information like disease state. Since a single sample can be used in multiple experiments and be subjected to different technologies and treatments, information regarding such methodology aspects generally appears on the experimental metadata.

Standardized descriptions for metadata, such as Minimum Information about a (Meta)Genome Sequence (MIGS/MIMS/MIMARKS), was first developed by the Genomic Standards Consortium (GSC). The goal of GSC standard is to promote mechanisms for standardization of description for (meta)genomes, including the exchange and integration of (meta)genomic data. As an example, attributes that describe human diseases require the Human Disease Ontology (DO). The DO database includes specific formal semantic rules to express meaningful disease models. To achieve the standardization of metadata, METAGENOTE offers features such as ontology search that enable users to describe their samples more precisely with standardized vocabulary. Metadata is validated according to the guidelines from the Genomics Standard Consortium (GSC), European Bioinformatics Institute (EBI), Earth Microbiome Project, and NCBI SRA. The following lists the sources and ontologies used in METAGENOTE for sample attributes.

Source of Ontologies

  • Disease Ontology: The Disease Ontology has been developed as a standardized ontology for human disease with the purpose of providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts.
  • BioPortal Metadata Ontology: This ontology represents the structure that BioPortal uses to represent all of its metadata (ontology details, mappings, notes, reviews, views).
  • Human Disease Ontology: The Disease Ontology has been developed as a standardized ontology for human disease with the purpose of providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts.
  • Experimental Factor Ontology: The Experimental Factor Ontology (EFO) is an application focused ontology modelling the experimental variables in multiple resources at the EBI and the Centre for Therapeutic Target Validation.
  • Environment Ontology: The Experimental Factor Ontology (EFO) provides a systematic description of many experimental variables available in EBI databases. It combines parts of several biological ontologies, such as UBERON anatomy, ChEBI chemical compounds, and Cell Ontology.
  • Foundational Model of Anatomy: The Foundational Model of Anatomy Ontology (FMA) is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems.
  • NGS Ontology: The NGSOnto ontology aims at capturing the workflow of all the processes involved in a Next Generation Sequencing, in order to ensure the reproducibility of a controlled and specific vocabulary.
  • Ontology for Biomedical Investigations: The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted.
  • Phenotypic Quality Ontology: Phenotypic qualities (properties). This ontology can be used in conjunction with other ontologies such as GO or anatomical ontologies to refer to phenotypes. Examples of qualities are red, ectopic, high temperature, fused, small, edematous and arrested.
  • Plant Ontology: The Plant Ontology is a structured vocabulary and database resource that links plant anatomy, morphology and growth and development to plant genomics data.
  • Uber Anatomy Ontology: Uberon is an integrated cross-species anatomy ontology representing a variety of entities classified according to traditional anatomical criteria such as structure, function and developmental lineage. The ontology includes comprehensive relationships to taxon-specific anatomical ontologies, allowing integration of functional, phenotype and expression data.
  • Food and Agriculture Organization: FAO provides soil information and knowledge on the different components and aspects of soils.
  • Country: The names of countries or areas refer to their short form used in day-to-day operations of the United Nations and not necessarily to their official name as used in formal documents.
  • Chemical Entities of Biological Interest: Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on small chemical compounds.
  • Omics Observation: OMICON is an emerging ontology which links interoperating semantic solutions for omic observation. This will federate existing ontologies which provide semantics for field sampling, wet lab work, sequencing, and in silico analysis.

Comments and Suggestions

If you have any comments or suggestions, please email us.

Bioinformatics and Computational Biosciences Branch (BCBB)
Office of Cyber Infrastructure and Computational Biology (OCICB)
National Institute of Allergy and Infectious Diseases (NIAID)
National Institutes of Health (NIH)
Rockville, MD 20852

Last updated on February 5, 2020.

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