Atlas Known Issues

The KPMP Atlas software team acknowledges that the tools may not always work ideally or the same from browser to browser. We want to acknowledge these issues for users and, if possible, provide potential workarounds until these issues can be resolved.

Have you run into an issue not reported here? Please report issues through our Give us your feedback link (above).

Open the Known Issues Tracker

Atlas Known Issues

The Atlas Explorer

The Atlas Explorer incorporates an easy-to-use search engine which allows users to search for markers or cell types of interest and view summary data visualizations across the following data types:

  • Single-nucleus RNA-seq
  • Single-cell RNA-seq
  • Regional transcriptomics

Summary of participants by data type

A summary of the data available in the Atlas Explorer is available on the Kidney Tissue Atlas homepage.

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.

Search by gene

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).

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.

Regional transcriptomics visualization page

Search by cell type

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.

Cell type search (Tubules tab)

Atlas Explorer

The Atlas Repository

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 is available 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 Atlas Spatial Viewer

The following data types have been incorporated into the Atlas Spatial Viewer:

For more details on these spatial technologies, refer to the Technologies help documentation under Imaging and Metabolomics.

The data available in the Spatial Viewer are routinely added as they are generated and quality checked. A summary of the data available in the Spatial Viewer can be found on the Kidney Tissue Atlas homepage.

The spatial images presented in the application have been pre-processed in order to convert them to OME (Open Microscopy Environment) TIFF (tagged image file format) using Bio-Formats bftools version 5.8.

Each dataset is identified by a sample ID, which is derived from a segment of a participant's biopsy tissue. Every sample ID may be traced back to a single participant ID.

NAVIGATION

The Atlas Spatial Viewer allows you to search the available KPMP spatial datasets by data-level and participant-level attributes and visualize the associated datasets.

Spatial Viewer home page

DATASET LIST

Filter panel

Narrowing your search to a focused selection of datasets is accomplished using the filter panel on the left-hand side of the screen. The filter panel is divided in two tabs, DATASET and PARTICIPANT, with each tab containing  attributes by which to filter the dataset list to the right of the filter panel.

Participant-level filters allow searching for datasets that contain particular participant-level attributes such as age range, tissue type, etc. Dataset-level filters allow a user to search for different types of datasets (Light Microscopy vs 3D Cytometry).

To open a dataset in the viewer, click on the link in the SAMPLE ID column.

Sorting and resizing columns

Click on a column heading to sort the data in the column ascending order. Click on the column header a second time to sort in descending order.

When hovering over the column heading you will see a blue line that appears at the right hand side of the column. Click and drag the blue line to increase or decrease the column width.

Showing/hiding columns

By default the dataset list displays the SAMPLE ID, DATA TYPE, and IMAGE TYPE columns. Click the left button at the top of the dataset list and a field chooser will appear which allows you show additional columns or hide the active columns. NOTE:e SAMPLE ID column cannot be hidden.

Participant information panel

Click on the Participant ID in the dataset list or when viewing an image to view the Participant Information panel. This panel contains clinical information (e.g. disease, age, eGFR) and data available within the Atlas for the selected participant.

Spatial viewer showing participant information panel

VISUALIZATIONS

The Spatial Viewer uses the Vitessce visualization platform as its visualization engine. The layout and features/functionality of the visualization page will be specific to the data type selected.


Light Microscopic Whole Slide Images

Visualization page showing a Light Microscopic Whole Slide Image dataset

Data Set panel

The Data Set panel on the left displays information on the selected image, including a reiteration of the type of the selected dataset (e.g. “RGB max projection of 8-channel immunofluorescence image volume.”) The Data Set panel also contains additional image information such as X and Y dimension, pixel size, number of channels, etc.

Spatial panel

In the Spatial panel, you can zoom in and out of the image by using the scroll wheel on a mouse or with a trackpad. To download the current image, click on the download icon in the upper-right corner of the Spatial panel.


3D Tissue Imaging and Cytometry

Visualization page showing a 3D Tissue Imaging and Cytometry dataset

Spatial Layers

For images with multiple channels, a Spatial Layers panel will appear under the Data Set panel. This panel allows you to control which channels appear, designate channel colors, adjust the z axis, and set the opacity of the image.


Spatial Transcriptomics

Expression Levels / Espression Histogram

Search for a gene of interest by typing the gene symbol of interest, select it, and the normalized expression level and corresponding number of cells will be graphed below in the Expression Histogram panel. Additionally, the Spatial and Scatterplot components will be updated to show the relative expression levels at different locations on the tissue.

Visualization page showing a Spatial Transcriptomics dataset

Lassoing/Selecting data

In both the Spatial view and the Scatterplot view, there are a few tools that allow you to select certain points and have them highlight on the other view. This can be especially helpful when looking at the expression levels on the scatterplot. If you see a grouping of spots you can see where they live on the tissue itself by using the lasso or box tool to select the points of interest.

Lasso/select tool used to select ares from either the spatial view or the scatterplot (UMAP) view

In order to clear your selection, simply reselect the gene of interest from the Expression Levels component on the left.

Search for a gene of interest by typing the gene symbol of interest, select it, and the normalized expression level and corresponding number of cells will be graphed below in the Expression Histogram panel. Additionally, the Spatial and Scatterplot components will be updated to show the relative expression levels at different locations on the tissue.

Spatial panel

The Spatial panel produces a heatmap showing the expression level for the selected gene on the various points on the tissue sample.

Scatterplot (UMAP) panel

Displays a scatterplot showing gene expression clusters and expression level for the selected gene as a heatmap.  

In the Scatterplot (UMAP) you can click the gear icon at the top in order to control a number of attributes on the scatterplot itself. The most useful control we have found is the ability to adjust the radius of the points in the scatterplot. In order to do this, you first change the Cell Radius Mode to Manual, and then you can adjust the slider to adjust the size of the points.

Scatterplot settings allows users to adjust the size of the cells by switching to manual mode and adjusting the scale of the cell size


CODEX (CO-DETECTION BY INDEXING)

Visualization page showing a CODEX dataset

Image metadata

The image metadata on the left conveys the following information specific to the image:

  • experimental strategy
  • tissue type
  • sample ID
  • participant ID

Data Set panel

The Data Set panel displays the image information for the image shown in the Spatial panel:

  • Image description/type (type)
  • file name/type of the downloadable image

Spatial Layers panel

For images with multiple channels, a Spatial Layers panel appears under the Data Set panel. It allows you to add or remove channels, allowing a maximum of six total channels at one time.

Click on the arrow next to the channel / marker name to choose from over 50 markers for the channels. You may also choose from eight different colors for your channels.

Spatial panel

Zoom in and out of the image by using the scroll wheel on a mouse or with a trackpad.

To download the current image, click on the download icon in the upper-right corner of the Spatial panel. 


SPATIAL METABOLOMICS, SPATIAL LIPIDOMICS, AND SPATIAL N-GLYCOMICS

METASPACE

Spatial metabolomics, spatial lipidomics, and spatial N-glycomics data visualizations are available via hyperlinks within the Spatial Viewer to metaspace2020.eu.

Users may select data to view as normal and then follow the active hyperlinks for the appropriate visualizations.

Figure: Metaspace platform displaying a spatial metabolomics dataset for a selected participant sample
Atlas Spatial Viewer

Atlas Ecosystem Releases


Q1 2024 (v13.0)

Data released to the Atlas Explorer (2):

  • Single-cell RNA-seq v1.5 (79 samples from 77 participants)
  • Single-nucleus RNA-seq v1.5 (80 participants)

Note: these datasets will also be available in CELLxGENE in early April 2024

Data released to the Atlas Repository (388):

  • 3D Tissue Imaging and Cytometry (63)
  • Clinical Data (1)
  • CODEX (104)
  • Imaging Mass Cytometry (60)
  • Single-cell RNA-seq v1.5 (1)
  • Single-nucleus RNA-seq v1.5 (1)
  • Spatial Lipidomics (2)
  • Spatial Metabolomics (48)
  • Spatial N-glycomics (16)
  • Whole Slide Images (91)

Data released to the Atlas Spatial Viewer (413):

  • 3D Tissue Imaging and Cytometry (115)
  • CODEX (26)
  • Imaging Mass Cytometry (77)
  • Spatial Lipidomics (10)
  • Spatial Metabolomics (96)
  • Spatial N-glycomics (17)
  • Light Microscopy Whole Slide Images (72)

Software Updates:

  • Overall
    • Minor cosmetic changes have been incorporated across the Atlas.
    • “Enrollment Category” has replaced the term “Tissue Type” when referring to enrollment disease cohorts  AKI, CKD, DM-R, and Healthy Reference. This change is intended to more easily differentiate how participants are categorized at enrollment in the KPMP study and categorized after the KPMP adjudication process.
    • Review the Known Issues Tracker for details of specific functionality issues, fixes, and workarounds.
    • Review the Data Change Log for details of specific data changes to any of the Atlas applications.
  • Explorer
    • Links to CELLxGENE for v1.0 and v1.5 of both Single-cell and Single-nucleus RNA-seq data
    • Link to GitHub for Single-nucleus RNA-seq pipelines
    • Adjusted p-value has been corrected in the Differential Expression tables for Regional Transcriptomics
    • Minor fixes for clarity of content
  • Atlas Repository
    • Minor display enhancements


February 2024

Data released to the Atlas Repository (3):

  • Primary Adjudicated Category
  • SomaScan Plasma Proteomics
  • SomaScan Urine Proteomics


December 2023 (v12.0)

Data released to the Atlas Repository (972):

  • Whole Slide Images (382)
  • 3D Tissue Imaging and Cytometry (297)
  • 10X Multiome (197) (note that there is some overlap among these files)
  • ATAC-Seq (132)
  • Single-nucleus RNA-Seq (107)
  • Spatial Transcriptomics (39)
  • Spatial Lipidomics (11)
  • Spatial N-glycomics (2)
  • Regional Proteomics aggregated analysis package (1)
  • Clinical Data (1)

Data released to the Atlas Spatial Viewer (642):

  • Light Microscopy Whole Slide Images (430)
  • 3D Tissue Imaging and Cytometry (165)
  • Spatial Lipidomics (44)
  • Spatial N-glycomics (3)

Software Updates:

  • Explorer Regional Proteomics - The Beta visualization of the Regional Proteomics data is now available in the Atlas Explorer. More features will be available for this data type in Q1 2024. 
  • Help menu - We have updated our Help menu in the upper right of the Atlas to show more detail of what resources are available to users.
  • Spatial Viewer - We have updated the Spatial Viewer to the most current version of Vitessce.


October 2023 (v11.0)

Data released to the Atlas Repository (1,721):

  • 10X Multiome (193) (note that there is some overlap among these files)
  • ATAC-Seq (132)
  • Single-nucleus RNA-Seq (99)
  • CUT & RUN (143)
  • Descriptor Scoring (1)
  • DNA Methyl-seq (120)
  • Single-cell RNA-Seq (50)
  • Biomarker Data: Stool Microbiome Metagenomics (2)
  • Regional Proteomics aggregated data package (1)
  • Whole Slide Images (579)
  • Segmentation Data (222)
  • Spatial Lipidomics (34)
  • Spatial N-glycomics (18)
  • Spatial Transcriptomics (319)
  • Clinical Data (1)

Data released to the Atlas Spatial Viewer (615):

  • Light Microscopy Whole Slide Images (422)
  • Spatial Lipidomics (129)
  • Spatial N-glycomics (24)
  • Spatial Transcriptomics (40)

Software Updates:

  • Repository Participant Information page - This panel, originally featured in the Spatial Viewer and containing participant-specific information (e.g. disease, age, eGFR), is now available in the Atlas Repository with even more information.
  • Spatial Viewer Recently Released - In the Spatial Viewer users may now click on the “Recently Released” check box on the File tab to select only those files that are new or updated in the current release.
  • Explorer formatting updates
  • Explorer now has a more clearly defined access to CellXGene for users looking for disease-specific differential expression analysis of the KPMP data.
  • The format of the gene expression tables has been updated for easier reading


June 2023 (v10.0)

New publications and their associated DOIs:

Data released to the Atlas Repository:

  • Single-cell RNA-Seq (50)
  • Regional Proteomics (118)
  • 10X Multiome (188) (note that there is some overlap among these files)
  • ATAC-Seq (123)
  • Single-nucleus RNA-Seq (99)
  • Whole Slide Images (80)
  • Opportunity Pool Biomarker Data:
  • Plasma Biomarker Data-BC AU5812-2022 (1)
  • Urine Biomarker Data-BC AU5812-2022 (includes timed urine information) (1)
  • Urine Biomarker Data-UHPLC MS_MS-2022 (includes timed urine information) (1)
  • Plasma Biomarker Data-UHPLC MS_MS-2022 ) (1)
  • Urine Biomarker Data-BC AU680-2022 (includes timed urine information) (1)
  • Spatial Lipidomics (corrected metadata spreadsheet) (1)
  • Updated open access clinical data file (includes DM-R) (1)

Data released to the Atlas Spatial Viewer:

  • Light Microscopy Whole Slide Images (80)
  • Spatial Lipidomics (corrected link) (1)

Software Updates:

  • Atlas Repository UI - The Atlas Repository user interface has been updated for consistency across Atlas applications and to allow for future enhancements.
  • CSV download - Filter the files you want and create a complete list of the files in a CSV. This will be helpful when making data requests or requesting DOIs be minted and associated with publications. The current CSV file is limited to 1000 rows due to technical issues we will resolve in Q3.
  • Diabetes Mellitus - Resilient (DM-R) - The tissue type of “Diabetic Nephropathy Resistor”, which was introduced in Q1 2023 has been relabeled to “Diabetes Mellitus - Resilient” (DM-R) to better reflect this participant group. As you may recall, these participants were originally under the CKD umbrella. You will now see this group addressed in all our filters along with CKD, AKI, and Healthy Reference tissue types.
  • File name identifier - The long identifier prefix on file names has been removed for better readability. It is still viewable if you select File UUID from the table column chooser.
  • Improved scrolling - Table and filter panel scrolling behavior has been improved for both Spatial Viewer and Repository
  • Recently Released - In the Repository you can now click on the “Recently Released” check box on the File tab to select only those files that are new or updated in the current release.
  • Participant Portal - Spanish language translation available


MARCH 2023 (v9.0)

ATLAS REPOSITORY

New data available

See: Atlas Data Release Notes

ATLAS SPATIAL VIEWER

New spatial data available:

  • Light Microscopy Whole Slide Images (196)
  • Spatial Lipidomics (86)
  • Spatial Metabolomics (25)
  • CODEX (6)

New feature - Participant Information:

By clicking on the Participant ID, in either the file list or when viewing an image, users will be able to view the Participant Information panel. This panel contains participant-specific information (e.g. disease, age, eGFR) and data available within the Atlas for that specific participant.

Spatial Metabolomics links updated

The links taking users out to METASPACE have been updated to direct users to a summary landing page for the sample selected. From there, users can navigate to the spatial views with detailed annotations of the data by selecting “Browse annotations”.


NOVEMBER, 2022 (v7.0)

ATLAS REPOSITORY

New data available

See: Atlas Data Release Notes


SEPTEMBER, 2022 (v6.0)

ATLAS SPATIAL VIEWER

New image types available

  • Spatial Metabolomics 
  • Spatial N-glycomics 
  • Spatial Lipidomics

ATLAS REPOSITORY

Changes to Participant ID display

  • When a file contains information for more than one participant, “Multiple participants” will appear in the participant column instead of the list of participants

New data available

See: Atlas Data Release Notes


JULY, 2022

Atlas Spatial Viewer

New image types available:

  • CODEX images for 11 participants

New data available:

  • Level added as a data type to be made viewable in the table 
  • 259 additional Whole Slide Images 

Software Applications Help documentation

  • Updated to include documentation on the CODEX images.

Atlas Explorer

Improved gene search

  • Allows two-letter gene searches.
    Please note that some two-letter genes may not show up in the search as there is a cutoff.
    Users can also search by known aliases that have more than two letters.

Atlas Release Notes

Atlas Data Releases


At KPMP we endeavor to maintain that high quality data be made available to our users. In this effort we will occasionally come across data that we have found requires it to be pulled back from the repository or replaced with corrections. We work closely with those that originally supplied the data to ensure not only that the data is replaced but that we also supply information as to why the data was pulled back or replaced.

View Atlas Data Change Log

Have you run into an issue with KPMP data not reported here? Please report issues through our Give us your feedback link (above).

Atlas Data Change Log

Atlas Known Issues

The KPMP Atlas software team acknowledges that the tools may not always work ideally or the same from browser to browser. We want to acknowledge these issues for users and, if possible, provide potential workarounds until these issues can be resolved.

Have you run into an issue not reported here? Please report issues through our Give us your feedback link (above).

Open the Known Issues Tracker

Atlas Known Issues

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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