GeoMx Microregional Spatial Transcriptomics

GeoMx microregional spatial transcriptomics detects high-plex protein and RNA expression within FFPE-embedded tissues to measure gene expression across the entire transcriptome. We combine this method with H&E and CyCIF images to select region of interests (ROIs) for GeoMX analysis.

About the Data Data Levels Explore Data

About the Data


Method and Protocol

Learn about the GeoMx method by reading:

Data Visualization

Full-resolution images can be viewed in a web browser using Minerva:

Learn more about the Minerva software at minerva.im.

Data Access

Data will be accessible from the following:

  • Levels 1: FASTQ (GEO)
  • Level 3: DCC (GEO)
  • Level 4: csv (AWS)

For a description of the files see the table below.

About the Samples

The following are planned to image with GeoMx:

  • 65 ovarian samples

Instruments

GeoMx data was collected on a Nanostring GeoMx Digital Spatial Profiler (DSP).

About the Data Generators

This data was generated and analyzed by the Laboratory of Systems Pharmacology at Harvard Medical School.


Data Levels

Data Type Description File Format Average size (per slide) Data Location
Level 1 Raw sequencing files FASTQ   GEO
Level 3 Count data for each collection plate DCC   GEO
Level 4 Log normalized gene expression data csv 150 MB AWS
All files Total per slide   12 GB  

Explore Data

Data Access and Data Visualizations

Click any of the following thumbnail images to access associated data or data visualizations. Data visualizations guide readers through the complexities of a large dataset through filters, search, or narrated image waypoints.

Ovarian STIC Spatial Transcriptomic Data from GeoMX and Multiplex Imaging

Curated Minerva Stories

Curated stories provide access to images that have undergone a quality control step to remove failed markers, ensure appropriate channel intensity settings, and provide metadata about the underlying sample and image. Click the Minerva story icon for an interactive view of the full-resolution images.

LSP17762
LSP17766