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The Pediatric Single Cell Cancer Atlas (PedSCAtlas) was developed by the Bhasin Systems Biomedicine Lab at Emory University in collaboration with the Aflac Cancer & Blood Disorders Center at Children's Healthcare of Atlanta. The atlas is located at https://bhasinlab.bmi.emory.edu/PediatricSC/. You can learn more about the methods used to develop the atlas in our 2021 blood asbtract presented at the ASH conference, Pediatric Single Cell Cancer Atlas: An Integrative Web-Based Resource for Single Cell Transcriptome Data from Pediatric Leukemias.
The PedSCAtlas allows for quick exploration, visualization of gene expression, and survival analysis of different pediatric solid and blood cancers without requiring extensive and time-consuming bioinformatics analysis and computational support.
There are currently five pediatric cancer datasets available on the atlas: Acute Leukemia, Wilms Tumor, Rhabdomyosarcoma (RMS), Ependymoma (EPN), and Premature Acute Lymphoblastic Leukemia (ALL). In addition to the pediatric cancer single cell and single nucleus datasets, the atlas also contains healthy young adult scRNA-seq bone marrow (BM) data combined with the acute leukemias data, healthy pediatric scRNA-seq BM data combined with the premature ALL dataset, and a separate adult healthy bone marrow scRNA-seq dataset accessible via the ImmuneCell module. For most cancer types, there is an accompanying bulkRNA-seq dataset accessible via the BulkExpression module. The modules will be explained in detail later. The excel table located here lists the RNA sequencing type, data source, disease type, number of samples, and number of cells associated with each PedSCAtlas dataset available currently.
For each pediatric cancer type, the following subtypes are available:
| Pediatric Cancer | Disease Subtypes |
|---|---|
| Acute Leukemia | Acute Myeloid Leukemia (AML) T-Cell Acute Lymphoblastic Leukemia (T-ALL) B-Cell Acute Lymphoblastic Leukemia (B-ALL) B/Myeloid Mixed Phenotype Acute Leukemia (B/My MPAL) T/Myeloid Mixed Phenotype Acute Leukemia (T/My MPAL) |
| Wilms Tumor | Anaplastic Wilms Tumor Favorable Wilms Tumor |
| Rhabdomyosarcoma (RMS) | Alveolar RMS (ARMS) Embryonal RMS (ERMS) |
| Ependymoma (EPN) | Supratentorial (ST) Posterior Fossa (PF) Spinal (SP) |
| Premature Acute Lymphoblastic Leukemia (pre ALL) |
Pre-B ALL High Hyper Diploid (HDD) Pre-B ALL t(12;21) (ETV6-RUNX1) Pre-T ALL |
There are currently five modules available on the atlas. Each module offers a different method to analyze the chosen pediatric cancer dataset.
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The SingleCell module allows users to visualize cell locations on a UMAP (Uniform Manifold Approximation and Projection) plot along with certain cell details (cluster id, cell type label, disease type, etc.), visualize gene expression or pathway enrichment on a UMAP or violin plot, and visualize statistical differences in pathway enrichment on ribbon plots.
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The ImmuneCell module allows users to visualize the expression of a gene in healthy adult bone marrow cells (including immune and hematopoietic stem cells) on a UMAP. This is useful to determine if a proposed blood cancer biomarker is malignant cell (or blast) specific or if it has expression in non-malignant cell types.
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The Biomarkers module allows users to explore pre-defined disease subtype biomarker sets and visualize their expression on UMAP or violin plots, grouped by different cell aspects.
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The BulkExpression module allows users to input gene names and visualize gene expression or gene set enrichment of bulkRNA-seq expression datasets for the chosen pediatric cancer type. Also, the module allows for survival analysis of the input gene or gene set, and produces a kaplan-meier plot and survival statistics based on survival association.
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The Prediction module is currently only available for the Acute Leukemia dataset, and allows for the prediction of leukemia subtypes of a user's samples based on bulk RNA expression input for those samples. The module uses an SVM classifier to predict each samples' leukemia subtype based on the expression of pre-determined leukemia subtype biomarkers.
Please see the Wiki User Guide page for detailed instructions and examples of how to use the PedSCAtlas.