Select inputs on left to show the number of donors that fall into different categories. By default, donors are shown from all programs listed on the x-axis.

Select inputs on left to show ridgeline plots of a continuous metric, separated by grouping.

Select checkboxes on the left to show a clustered heatmap of donors based on different continuous metrics (e.g. age, BMI). Metrics are provided for all donor programs for which they are available. For more information about each program, see here. For more information about each donor, explore the Data Library.

Select checkboxes and correlation type on the left to show the correlation between different metrics for PanKbase donors. The correlation coefficient (R for Pearson's correlation and Rho for Spearman's correlation) is denoted by the color and number inside the box, and the p-value is indicated by the asterisks. Significance levels are as follows: * p < 0.05, ** p < 0.01, *** p < 0.001. P-values are re-calculated for multiple comparisons based on the number of comparisons selected using the checkboxes.

Select inputs on the left to create a scatter plot showing the correlation between two metrics.

Select metrics on the left to calculate and plot a principal component analysis (PCA) of the donor metadata. Each point in the plot represents one donor. For more information about each donor, explore the Data Library.

Select a principal component (PC) to show the contribution of different variables to that PC (i.e. how much does that metric influence the PC?) based on the plot above.

Browse which assays are available for which donors. For more information about each donor, explore the Data Library.

Select checkboxes on the left to see the number of donors with data available for specific combinations of assays. Important! These intersections are inclusive (e.g. if a donor has Genotyping, scRNAseq, and RNAseq data available, they are included in the count for Genotyping+scRNAseq as well as the count for Genotyping+scRNAseq+RNAseq. This means that an individual donor may be represented in multiple intersection groups. For more information about each donor, explore the Data Library.

Select inputs on the left to see the total number of donors who have data for each assay type by the grouping variable. For more information about each donor, explore the Data Library.

Venn Diagram of auto-antibody (AAB) positivity for donors positive for at least one AAB. Currently displayed donors are from the Human Pancreas Analysis Program (HPAP) . For more information about each donor, explore the Data Library.

Assays included in the Donor Summary Tool are defined as follows:

scRNA-seq: single cell measurement of gene transcript abundance
snATAC-seq: single cell measurement of accessible/open chromatin
HLA typing: serological or genetic measurement of human leukocyte antigen types
Genotyping: measurement of genetic information either my microarray or sequencing
Function: measurement of pancreatic islet function, for example perifusion
RNA-seq: bulk measurement of gene transcript abundance, either from tissue or sorted cells
ATAC-seq: bulk measurement of accessible/open chromatin, either from tissue or sorted cells
WGBS: measurement of methylated DNA based on bisulfate sequencing
Morphology: measurement describing the size, shape, and structure of a tissue and/or cells within a tissue
CyTOF: single cell measurement of protein markers based on mass cytometry
Imaging: measurement describing the location and abundance of specific molecules within a tissue by imaging techniques
Histology: measurement describing the anatomy of a tissue based on microscopy
CODEX: measurement of protein markers in tissue samples using spatial multiplexed imaging
Imaging mass spec: measurement of molecules in tissue samples using mass spectrometry
Single cell multiome: paired single cell measurement of gene transcript abundance and accessible/open chromatin
BCR-seq: paired single cell measurement of B cell receptor sequence and gene transcript abundance
TCR-seq: paired single cell measurement of T cell receptor sequence and gene transcript abundance
CITE-seq: paired single cell measurement of surface protein markers and gene transcript abundance
Flow cytometry: measurement of physical and/or chemical characteristics of cells in a sample, for example to quantify cell type abundance