What is metadata?

Metadata provides contextual information about your samples, such as:

  • Collection details (e.g., date, location, method)
  • Sample type (e.g., stool, soil, wastewater)
  • Experimental variables (e.g., treatment groups, timepoints)
  • Demographic details (e.g., age, sex, BMI, clinical data)

Adding metadata enhances the power of your analysis by enabling cohort creation, comparative studies, and advanced statistical modeling.

Best Practices for Metadata Upload

  1. Consistent Identifiers: Ensure your metadata variables are consistent across groups
  2. Comprehensive Details: Include as much metadata as possible to support robust downstream analyses.
  3. Regular Updates: Keep your metadata files up-to-date, especially for longitudinal studies.
  4. Group Wide-Ranging Continuous Variables: if you have a wide-ranging numerical value for metadata (e.g., ages ranging from 0-60), consider grouping them into categories (Age: 0-18years, 19-39 years, 40-60years). Pick relevant ranges according to your study.

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Video walkthrough of Metadata import and generating comparative analyses using it

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Adding your Metadata

Metadata can be added or edited for one or more samples by selecting them in the “Cohorts and Metadata” Menu and clicking “Edit Metadata”. Depending on the number of samples selected, you will be prompted to edit metadata categories through a pop-up (Single Edit) or a template .CSV file (Batch Edit).

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Editing Single-Sample Metadata

When Editing Metadata for a single sample, a pop-up window will appear to edit default metadata or New Custom Fields.

Enter a text/numeric/datetime value for relevant metadata categories, or add a new metadata category by selecting “Create Custom Field”.

Click “Save” once complete to view the updated metadata in the sidebar.

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Editing Multi-Sample Metadata by Template Batching

When Editing Metadata for multiple samples

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Filling up the Metadata CSV Upload Template Form:

At the upload stage, you will be asked to download a Metadata CSV Form for all of your samples. The form is in long format with columns representing your different samples and rows representing your metadata fields. The first two rows needs to stay constant and are not modifiable. From Third row till Fifteenth row represents system metadata fields which are optional fields to fill out if its relevant to your project. Fields that needs to be filled out for custom metadata are

  • Second Column and Fifteenth row onwards:- Custom Metadata Field Label without any special characters and spaces
  • Third Column and Fifteenth row onwards - Custom Metadata Data Type. It can be either “Text” or “Decimal” (Numbers or Numerics)
  • Fifteen Column and Onwards - Custom Metadata values for your respective samples

Metadata & Cohorts Menu will allow you to

  • filter your dashboard view using custom metadata fields you uploaded for your samples
  • Add tags to your samples for filtering your dashboard view
  • Add Additional Metadata fields for your samples from the dashboard view
  • Generate Comparatives by splitting cohorts automatically based on your uploaded metadata and folder structures as well.

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Filtering your Dashboard View with Custom Metadata Fields:

Cosmos-Hub allows you to filter your dashboard view on the Cohorts & Metadata menu by using your uploaded custom metadata fields. The video down below gives you a short demonstration on how to use this functionality for your use-case.

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Adding Tags to your samples and filtering your dashboard view with Tags:

Cosmos-Hub allows you to add Tags to your samples for filtering your dashboard view on the Cohorts & Metadata Menu with Tags. The video down below gives you a short demonstration on how to use this functionality for your use-case.

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Adding Custom Metadata fields from the dashboard of the Cohorts & Metadata Menu:

From the Cohorts & Metadata Menu, you can add custom metadata fields for your samples as well if you skipped the metadata upload part from the Upload menu. You can add custom fields for individual samples through the UI or add custom fields for multiple samples using the Metadata Upload CSV Template form. The video down below gives you a short demonstration on how to use this functionality for your use-case.

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Generating Comparatives and splitting Cohorts automatically using your custom metadata fields as well as your Folder Structure:

Cosmos-Hub allows you to generate comparatives automatically using automated cohort splitting instead of selecting each sample manually for different cohorts. The video down below gives you a short demonstration on how to use this functionality for your use-case.

The results for the comparative analysis can be viewed from the Comparative Analysis Section on the menu. The video down below gives you a short demonstration on how to navigate to the Comparative Analysis Results and explore the results.