The KPMP Data Visualization Center (DVC) has developed a variety of internal and external applications to support the gathering, integration, and display of the data generated through this project. All software is freely accessible from our KPMP GitHub page.

Source Code

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The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

Data

Three data types have been incorporated into the first version of the Atlas Explorer: single-nucleus RNA-seq, single-cell RNA-seq, and regional transcriptomics.

Total participants in Atlas Explorer v1.0 for each data type

OMICS TYPE HEALTHY REFERENCE CKD AKI
Single-nucleus RNA-seq (snRNA-seq) 3 10 6
Single-cell RNA-seq (scRNA-seq) 0 15 12
Regional transcripomics (LMD RNA-seq) 9 22 5

The single-nucleus and single-cell datasets are described in detail in this preprint (Note: the v1.0 Atlas Explorer includes only a subset of the samples described); the manuscript also details the approach to assigning cell types to the clustered data.

The cell types noted in the application were established as a joint effort with the HuBMAP Consortium. The HuBMAP ASCT+B Reporter tool can be used to visualize the  anatomical structures, cell types, and biomarkers (ASCT+B) authored by the domain experts. The cell types and anatomical structures are also being represented in the Cell Ontology and Uberon, respectively.

Navigation

The Atlas Explorer allows users to search by genes, cell types, or supported technologies and see the associated data.

Gene Search

Searching for a gene presents the user with various visualizations and data tables displaying how the gene is expressed in the selected data type.

Choosing the single-nucleus or single-cell RNA-seq data types yields a visualization page with a "reference UMAP" showing how the full dataset was clustered as well as the inferred cell type/state of each cluster (see this preprint for more details on the clustering and cell attribution methods); a feature plot showing the expression of the selected gene, and a table detailing the expression of the selected gene in each cluster (compared to all other clusters) (Figure 1). Users can also filter the dataset down to only include AKI, CKD, or healthy reference samples - this updates the gene feature plot and the table (but not the reference UMAP image).

Figure 1: Navigating the Atlas Explorer visualization page

Searching for a gene and choosing the regional transcriptomics data type yields a visualization page with a "bubble plot" showing the expression of the selected gene across all tissue types (AKI, CKD, and healthy reference tissue) and microdissected regions, and a table detailing the expression of the selected gene in each region compared to all other regions (Figure 2). Users can also filter the dataset down to only include AKI, CKD, or healthy reference samples.

Figure 2: Regional transcriptomics visualization page

Cell Type Search

Users can also begin their search with a cell type instead of a gene. After searching for a cell type or selecting one from the renal corpuscle or nephron schemata (Figure 3), a user can see all of the data currently mapped to that cell type. As of Atlas Explorer v1.0, the available data will be single-nucleus and single-cell clusters or microdissected regions. After choosing one of the clusters/regions, users are presented with a table showing which genes are most differentially expressed in the selected cluster/region.

Figure 3: Cell type search (Tubules tab)

Atlas Explorer

Data

The Atlas Repository provides access to the datasets being generated by KPMP. The datasets available in the repository are a combination of raw and processed data from KPMP participant biopsies and reference tissue samples. Datasets are routinely added as they are generated and QCed. Some data files shown in the repository are "controlled access", meaning they can only be retrieved after a data use agreement is in place between KPMP and your organization. A summary of the data available in the repository can be seen on the Kidney Tissue Atlas homepage.

Navigation

Users can search for datasets using the filter panel on the left-hand side of the screen. There are two different facets available for searching and filtering: by Participants and by Files.

 Navigating the Atlas Repository

Participant-level filters allow a user to search for files that contain particular participants or participants with various attributes (e.g. sample type, tissue type). File-level filters allow a user to search for different types of files, such as certain file formats or experiment types.

Atlas Repository

The KPMP Data Visualization Center (DVC) has developed a variety of internal and external applications to support the gathering, integration, and display of the data generated through this project. All software is freely accessible from our KPMP GitHub page.

Source Code