ㅤ
Companion Website for "Constructing and Using Cell Type Populations for the Human Reference Atlas"
Andreas Bueckle1,4,**, Bruce William Herr II1, Lu Chen2, Daniel Bolin1, Danial Qaurooni1, Michael Ginda1, , Kristin Ardlie3, Fusheng Wang2, Katy Börner1,*
1 Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
2 Department of Computer Science and Department of Biomedical Informatics, Stony Brook University, Stony Brook, 11794, NY, USA
3 Broad Institute, Cambridge, 02142, MA, USA
4 Lead contact
* Correspondence: katy@indiana.edu, X: https://twitter.com/katycns
** Correspondence: abueckle@iu.edu, X: https://twitter.com/AndreasBueckle
Link to paper on bioRxiv (forthcoming)
Link to hra-pop GitHub repository
Link to HRApop graph data on HRA LOD server
Link to Atlas Enriched Dataset Graph
Link to Anatomical Structures (AS) Cell Summaries
Link to HuBMAP Portal
Link to CZ CELLxGENE Portal
Link to GTEx Portal
Link to SenNet Portal
Link to HRA Workflows Runner
Link to HRA Workflows
HRApop extraction sites
Assigning a spatial location via the Registration User Interface (RUI, https://apps.humanatlas.io/rui) is an essential requirement for a dataset to be included in HRApop. Below is an instance of the Exploration User Interface (EUI, see federated version with all registered tissue blocks here) that only shows extraction sites for datasets in HRApop.
Interactive 3D visualization of cell type populations for outer cortex of kidney
This 3D visualization shows 36 unique cell types with a total of ~6,000 cells. These are found in these anatomical structures based on experimental data registered into them (for performance reasons). A 5x5x5 mm tissue block is shown for scale. Please click and drag your left mouse button to rotate the camera around the kidney; click drag the right mouse button to pan; use the mouse scroll wheel to zoom in and out. Code to demonstrate how 3D cells can be generated with Python is available here. LOAD button to take user to interactive 3D visualization.
Code to demonstrate how 3D cells can be generated with Python is available here.
Interactive Sankey Diagram
Atlas-level data for HRApop v0.10.0 comes from various sources and . The Sankey diagram below offers an overview of the distribution of HRApop datasets along demographic, informatical, and biomedical markers.
Single-cell proteomics data
For HRApop v.10.1, the HRA Workflows Runner handled the download, annotation, and summary of single cell (sc-)transcriptomics datasets; cell summaries for sc-proteomics datasets were compiled on Github at https://github.com/cns-iu/hra-ct-summaries-mx-spatial-data/tree/main. The HRApop Construction and Enrichment Pipeline gathered cell summaries for these datasets from there. Each dataset features a cell type for each cell but also individual coordinates.