Tool:Simplify Your Sample Annotation and Submission Using METAGENOTE
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4.7 years ago

The National Institute of Allergy and Infectious Diseases (NIAID) Bioinformatics and Computational Biosciences Branch is pleased to announce the release of METAGENOTE, a tool developed to greatly streamline the proper sample annotation and submission of metadata with the associated sequencing files to the NCBI Sequence Read Archive (SRA) database.

METAGENOTE refers to the collection of METAdata of GEnomics studies on a web based NOTEbook. This tool is helping researchers to: 1) comply with the scientific journals' requirements for sharing of genomic data no later than at the time of publication; and 2) enrich genomic data with structured vocabulary to facilitate future integration of multiple studies and reproducibility.

Unfortunately, most researchers still find the conventional annotation and metadata publishing processes very cumbersome. The metadata that is typically needed includes attributes such as: sample ID; collection date; tissue source; organism; treatment; and sequencing method. METAGENOTE’s user interface includes frequently used words, an anatomy selection diagram, and integrated ontologies for a much simpler annotation process for any type of genomic sample with associated sequencing files.

METAGENOTE offers additional features for handling metadata:

  • Fast import of metadata from users' Excel files (if available)
  • Easy sharing of annotated sample group tables with lab members
  • Annotated drafts stored in a user’s workspace until ready for publication

Perhaps the feature that is most attractive to researchers is the integration with the NCBI SRA submission API. In METAGENOTE’s submission workflow, users select the sample group table they wish to publish, then drag-and-drop sequencing files into the browser for automatic transfer to the NCBI SRA, along with the creation of BioProject, BioSamples, and SRA experiments.

COVID-19 genome metadata sequencing • 974 views
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METAGENOTE can be used to submit SARS COV-2 sequencing files to the NCBI Sequence Read Archive (SRA) database.

A new demo video has been uploaded to the NIAID Bioinformatics YouTube channel: https://youtu.be/TLjcASgsm_8

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