A web-based analysis platform to use your data products

Investigate across data types with multiple data products. Use self-service analysis apps to generate, store, and share useful data artifacts (UDATs).

A single source for your data and analysis apps

Data products built from data nodes

  • Align and organize multiple data products in one platform
  • Integrate public data with proprietary data
  • Analyze distributed data in one virtual location
  • As new data arises, you can rapidly develop and deploy new data products
  • Data products are updated on your preferred schedule, keeping your data and analyses current, versioned and reproducible
  • Reduce data inconsistency and duplications
  • Each data product comes with analysis apps which are tailored to that dataset

More on Data Nodes

Interactive analysis apps

  • Gain autonomy over your data analysis process within a guided environment
  • Confidently ask and answer your own questions by running, iterating, and re-running analyses in your own terms
  • Use intuitive and powerful analysis apps to run simple and complex analysis algorithms and produce results
  • Use and reuse R/Python scripts created by your data scientists as analysis apps

See the Algorithms
See Apps for Life Sciences
See Apps for Healthcare

Parameterize without coding

  • Design a cohort dynamically – observe the changes in your cohort size with every selection
  • Analyze your cohorts using point-and-click parameter selection
  • Use the search function to easily find your parameter of interest from large collections
  • Instantly iterate on analysis by modifying your previous set of parameters to generate a new set of results

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Accessible useful data artifacts (UDATs)

  • UDATs are digital objects create when you or an algorithm analyze the data
  • Examples of UDATs are cohorts, analysis results, and groups of variables that represent gene signatures or risk scores
  • UDATs are automatically saved with provenance, making them easy to reproduce and use in subsequent analyses

Learn More About UDATs


  • Re-run analyses from UDATs and share them with anyone on your team
  • Sharing reduces redundant work
  • UDATs support data-driven decisions, maximizing productivity and efficiency
  • The transparent and executable history facilitates retention of institutional knowledge

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A Clinical Data Mesh for Quality Improvement and Research in Healthcare

In this Campus LISA webinar, you will learn how you can utilize data mesh for healthcare. Panelists include: Mike Hogarth, Mark Mooney, and Tom Covington.

Analysis Examples

R Integration

Python Integration

UMAP & Clustering

Cox Survival

Pathway Analysis

Cohort Comparison

“I feel like a data superhero!”

– Michelle Mourad, MD,
Vice Chair of Clinical Affairs and Value, Department of Medicine,
Medical Director, Transitions in Care, UCSF Health

How to Run an Analysis

Running an analysis in Tag.bio is as simple as choosing a data node (data product), selecting an analysis app, setting the parameters, and hitting “run”.

See Apps for Life Sciences See Apps for Healthcare

See Life Sciences Solutions

See Healthcare Solutions

More platform features

These features are designed to help you and your team easily uncover patterns and outliers in your data.

Dynamic cohort creation
Point-and-click to re-parameterize
Reproducible analyses
Download data slices and analysis results
One-click sharing
Run follow-up analysis
Entity annotations
Add UDATs to your favorites
Leave notes on analysis results
Let’s get the conversation started

From a 30-minute demo to an inquiry about our 4-week pilot project, we are here to answer all of your questions!