Getting Started

Quickstart FaceBase Data Philosophy

Using FaceBase

Key Concepts for FaceBase Users Browsing and Filtering Data Visualizations in FaceBase Data Sharing and Citing Data Exporting Data from FaceBase Accessing Data Programmatically Using 3D Viewers Viewing NIfTI files Converting TIFF to OME-TIFF (using Bio Formats)

Controlled Access Human Data

Controlled Access Human Data - Policy and Requests A. Read and complete the Data Use Certificate Agreement (DUC) B. Complete the online Data Access Request (DAR) form (An IRB is required) C. Select the Requested Datasets D. Print, Gather Signatures and Submit the DUC and DAR forms E. Receive notification and further instructions F. Create and upload your encryption keys G. Renew access

Submitting Data - Basics

Video Tutorials for Contributors Key Concepts for Data Contributors Data Submission Process Creating a Dataset Creating Experiments, Biosamples, and Replicates Uploading Data Files Quality Control Rules Releasing Your Dataset Self-guided Tutorial

Submitting Data - Advanced

Using the Annotations Editor (2D images) Defining Surface Models (3D models) Linking Thumbnails to Files

Tools

DERIVA Tools - Bulk upload and export

Support

Getting Help FAQs

Visualizations in FaceBase Data

This page is a work in progress.

The FaceBase system includes pipelines that convert data of a specific resolution and format into helpful visualizations that can deepen a user’s experience with the data. Such visualizations include: Image Volumes, Histology/Annotations, Surface Mesh and Single Cell viewers.

Recommended viewing: Imaging Data in FaceBase

Image Volume Viewer (3D images)

Figure 1: TBD

Some imaging data is created in three dimensions, which is useful in understanding the shape and size of specific anatomical regions of the face and skull, for example when comparing control specimens with mutant specimens.

Where a 3D image has been contributed, FaceBase provides a downsampled 3D preview inside your browser window. Use the following dataset to try it out - TKT - microCT - Soft Tissue of Msx1 Control Mice at E16.5:

Scroll down to the Downsampled Image Previews section.
You have the option to click the “Full Screen” button for a larger view.
Click the “Click here to load image”.
Once the image loads, you can make the following adjustments:
- Use your mouse to turn the 3D image in all directions and to zoom in and out.
- The panels on the right side provide different views of the image. Use the sliders in each panel to step through slices of the image.
On the left side, hover over the “Volume” label to open the Volume panel where you can adjust the levels or brightness of the planes to virtually examine the structures in the image.

Check out this video that demonstrates how to use the Image Volume Viewer.

Histology/Annotations Viewer (2D images)

Figure 2: Example of 2D image in default view (Scale at 100mm)

Two dimensional images in the FaceBase repository are commonly histological (stains are used to show regions where a gene is expressed). Our pipeline accepts the raw image file from a microscope and converts it into an image may be viewed in a web browser page (Figure 1). The viewer is like an online, digital microscope, allowing the user to zoom in for a deep view of the image (depending on the resolution of the image - the higher the resolution, the more deeply you can zoom in, see Figure 3).

To download a screenshot of the current view that includes an accurate scale, click Take a Screenshot. This is ideal for use in publications and presentations.

Figure 3: Example of the same image zoomed in (Scale at 20 mm)

Use the following dataset as an example: 1-SXC4 - Histology and schematic overview of mouse molar root development:

Scroll down to the Imaging Data section (or use the links on the left side of the page)
Click View for one of the imaging records.
Click Full screen to enlarge the viewer.

Annotations

Figure 4: Example of an annotated image

Our viewer also supports annotations of anatomical regions in an image (see Figure 4). Annotations link to the corresponding FaceBase anatomy page for that region, which displays more information on the region and lists any related data in the FaceBase repository.

To see if an image already has annotations, click Show Annotations.

Data contributors can use editing tools to mark a colored boundary around specific anatomical regions on an image, label them (see Figure 5). Click here for documentation on annotating images.

Figure 5: Example of the Annotations Editor

Surface Mesh Viewer

Figure 6: Example of the Surface Mesh Viewer

If a contributor provides surface mesh data - which depicts surfaces of interest - our Surface Mesh Viewer can create a ‘jigsaw puzzle’ effect where each surface mesh object is given its own color and channel, which can be toggled on and off (see Figure 6). Surface meshes may be annotated with anatomical landmarks demarcating specific locations on a specimen. The distance between landmarks can also be calculated.

This educational tool is especially powerful for new researchers to learn anatomical regions.

Use the following dataset as an example: 3V4A - E18.5 wildtype mouse microCT

Scroll down to the 3D Surface Models section.
Click Full Screen if you’re on a smaller display.
Use the following buttons to explore the image: Zoom In, Zoom Out, Rotate.
Click Meshes to open a panel of anatomical regions identified in the image.
- Click the colored dots to toggle visibility on and off for that region.
- Click an anatomical term to open the related Anatomiy page that lists all related datasets.

View all available Surface Mesh Model imaging data available in FaceBase.

Check out this video that demonstrates how to use the Surface Mesh Viewer.

Single Cell Viewer (scatter plot of scRNA-Seq)

Figure 7: Example of the Single Cell Viewer

Unique to FaceBase is the ability for contributors to upload their sequencing data and receive a processed visualization of their data (see Figure 7). Single-cell RNAseq data from FaceBase datasets can be visualized by the UCSC Cell Browser and interactive viewer for single cell expression, where you can easily identify cell clusterings and gene-expression patterns.

Use the following dataset as an example: 1-YSFP - Single cell transcriptomics of the talpid2 avian mutant mandibular prominence

Scroll down to the Processed Data section and browse the rows.
Rows for R data (such as a Seurat object) display a thumbnail of a scatter plot. Click View Details for one of these rows.
When you open the record, scroll to the Cell Browser area to view the embedded UCSC Cell Browser viewer for this data. You can click Full Screen for a larger presentation if you’re using a laptop, for example.
Access the Interactive Tutorial: At the menu at the top of the viewer, click Help and then Tutorial.