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

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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.

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.

This is a link

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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

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

Data

The following data types have been incorporated into the Atlas Explorer:

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

Participants in Atlas Explorer for each 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.

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

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.

Figure: 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: The SAMPLE ID column cannot be hidden.

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

Figure: 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

Figure: 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.

Figure: 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.

Figure: 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.

Figure: Shows tool within Scatterplot view allowing users to adjust the size of the cells my switching to manual mode and adjusting the scale of the cell size

CODEX (CO-DETECTION BY INDEXING)

Figure: 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 Tools Releases


NOVEMBER, 2022

Atlas Ecosystem Release v7.0

ATLAS REPOSITORY

New data available

See: Atlas Data Release Notes section


SEPTEMBER, 2022

Atlas Ecosystem Release 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 section


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

Data Released to Atlas Repository


DECEMBER, 2022

Atlas Data Repository Release v5.4.1

Opportunity Pool Biomarker Data

The SomaScan Plasma biomarker data (Plasma Biomarker Data-SomaScan-2022.zip) has been temporarily removed from the Atlas Repository until further QC is completed. 

 

Clinical File

A bug fix has been implemented correcting an error in calculating baseline eGFR for AKI participants. The change was made for column ‘Baseline eGFR(ml/min/1.73m2) (Binned)’. This is not an issue in prior releases, only the November 2022, v5.4 release of the clinical file.

NOVEMBER, 2022

Atlas Data Repository Release v5.4

Opportunity Pool Biomarker Data

Each data type is downloadable as an individual zip package containing:

  • Protocol and documentation file(s) from each lab that ran the experiments
  • Documentation from KPMP Biomarker Quality Control Working Group (BQCWG) describing QC steps and Data dictionary for data file
  • Coefficient of Variation file from the KPMP BQCWG

Opportunity pool biomarker data packages
Sample counts
Plasma Biomarker Data-MSDQ120-2022.zip
18 Healthy Reference / 119 AKI or CKD
Urine Biomarker Data-MSDQ120-2022.zip
18 Healthy Reference / 119 AKI or CKD
Plasma Biomarker Data-SomaScan-2022.zip
18 Healthy Reference / 119 AKI or CKD

Number of files in Atlas Repository

Data type
Added in this release
Total in repository
3D Tissue Imaging and Cytometry
8
64
Spatal Transcriptomics
64
176
Biomarker data
3
73

DOI collections

DOI doi.org/10.48698/3z31-8924 has been associated with KPMP files used in "An atlas of healthy and injured cell states and niches in the human kidney" from Lake et. al. (see https://www.kpmp.org/doi-collection/10-48698-3z31-8924 - for data download link)

Clinical File

Updated as of October 24, 2022


SEPTEMBER, 2022

Atlas Data Repository Release v5.3

Data type
Added in this release
Total in repository
Single-cell RNA-Seq
112
706
Single-nucleus RNA-Seq
186
1105
Whole Slide Images
167
1267
Regional Transcriptomics
173
319
Bulk total/mRNA
134
153
3D Tissue Imaging and Cytometry
56
Spatial Transcriptomics
128
128
CODEX
43
43
Clinical data file
1
1
Total for release
944
3,778


JUNE, 2022

Data Changes

Slides were found to be mislabeled either based on stain, frozen sample, or incorrect sample ID. The following slide image files have been renamed to accurately reflect their contents:

Participant ID 
Original file name
Updated file name
Date changed
30-10123
ae89038a-ddb5-41b2-b3a1-c96bd6b42a82_S-1908-009769_HE_3of3.svs
ae89038a-ddb5-41b2-b3a1-c96bd6b42a82_S-1908-009769_FRZ_1of1.svs
11/30/2021
30-10123
ee5dc96e-ee11-437f-a139-649af366ef50_S-1908-009768_HE_2of3.svs
ee5dc96e-ee11-437f-a139-649af366ef50_S-1908-009768_HE_2of2.svs
11/30/2021
30-10123
817ed691-b6f5-4db6-84e9-694ee2980054_S-1908-009767_HE_1of3.svs
817ed691-b6f5-4db6-84e9-694ee2980054_S-1908-009767_HE_1of2.svs
11/30/2021
31-10091
9c365bef-7224-4abc-ab04-05c5d0cc5635_S-2006-004818_HE_1of2.svs
9c365bef-7224-4abc-ab04-05c5d0cc5635_S-2006-004818_FRZ_1of2.svs
5/19/2022
31-10091
860124c6-7bc9-4e81-b17e-d0ad750fc3c2_S-2006-004819_HE_2of2.svs 
860124c6-7bc9-4e81-b17e-d0ad750fc3c2_S-2006-004819_FRZ_2of2.svs
5/19/2022
28-11515
81000959-3651-434b-8aa9-76db4799a688_S-2002-007608_HE_1of1.svs
81000959-3651-434b-8aa9-76db4799a688_S-2002-007608_FRZ_1of1.svs
5/19/2022
31-10097
adf8ab0b-9998-4a34-9e79-18d2d56c3d2a_S-2103-004670_HE_1of1.svs
adf8ab0b-9998-4a34-9e79-18d2d56c3d2a_S-2007-002695_HE_1of1.svs
5/19/2022


Atlas Data Release Notes

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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