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Table 3 Queries and functions built into the database

From: Rapid single cell evaluation of human disease and disorder targets using REVEAL: SingleCell™

HCA whitepaper requirements

Functionality

Functionality in Reveal: SingleCell

At least one developer-oriented portal providing a platform (e.g. FireCloud or Toil) in which developers can bring containerized environments to perform analyses on the data

 

R & Python API allow users to work in R studio or Python and directly select data from REVEAL: SingleCell

At least one user-oriented portal providing interactive interfaces to the data; for example:

 

R & Python API

 

Quantifying the expression of a given gene (e.g., marker genes specified by user) across cell types, shown in several popular modalities (e.g., low-d plots, heatmaps, violin plots)

SingleCellviewer and Plotly connecting to REVEAL: Singlecell R & Python API

 

Showing clustering of individual cells from an experiment based on expression profiles;

R & Python API clustering routines

 

Painting cell clusters (ordinations) by metadata (technical and experimental) to identify batch effects and visualize biological groupings (depending on the type of metadata);

SingleCellviewer and Plotly connecting to REVEAL: Singlecell R & Python API

 

Visualizing gene signatures by several modalities, including heatmaps and dot plots of average expression by cell group; and

SingleCellviewer and Plotly connecting to REVEAL: Singlecell R & Python API

 

Cross-correlating gene expression with epigenetic markers.

Using the REVEAL: SingleCell R & Python API

Multiple query-oriented portals with APIs targeting custom access patterns, for example: Tag based queries

  
 

Querying all gene expression tables generated with a particular analysis

Using the REVEAL: SingleCell Rest API & R notebook

 

Querying all cells for those that match the expression pattern of a target cell and return the metadata for the matching cells

Using the REVEAL: SingleCell Rest API & R notebook

 

Querying all raw data for a specific tissue type, ranked based on a custom combination of quality-control metrics.

Using the REVEAL: SingleCell Rest API & R notebook

Housekeeping requirements

  
 

Loading data

Using the REVEAL: SingleCell Rest API & R notebook

 

Adding tags after data load

Using the REVEAL: SingleCell Rest API & R notebook

 

Deleting data

Using the REVEAL: SingleCell Rest API & R notebook

  1. Legend: The requirements listed in the HCA whitepaper take two forms: actual queries and visualization capabilities. The R and Python APIs support the visualization requirements. The REST API and R notebook support the queries. We included the housekeeping requirements in the list because those are essential capabilities for a database