Show Notes
Hawkins AG et al., Cell Genomics - This episode summarizes Hawkins et al.'s presentation of the Single-Cell Pediatric Cancer Atlas (ScPCA) Portal, a publicly available resource that provides uniformly processed sc/snRNA-seq data and standardized metadata for pediatric tumors. The Portal hosts summarized expression data for over 700 samples across 55 pediatric cancer types, downloadable as SingleCellExperiment or AnnData objects and accompanied by QC reports, automated and curated cell-type annotations, and CNV estimates. The team also introduces scpca-nf, an open-source Nextflow workflow using alevin-fry for efficient, reproducible processing and support for additional modalities such as CITE-seq, cell hashing, bulk RNA-seq, and spatial data. The resource aims to accelerate pediatric cancer research by reducing reprocessing time and enabling cross-sample analyses. Key terms: single-cell RNA-seq, pediatric cancer, data portal, scpca-nf, alevin-fry.
Study Highlights:
The ScPCA Portal aggregates uniformly processed sc/snRNA-seq data for over 700 samples spanning 55 pediatric cancer types and provides downloads ready for analysis in R and Python. Data are processed with an open-source Nextflow workflow (scpca-nf) that uses alevin-fry for fast quantification and includes QC, dimensionality reduction, consensus cell-type annotations, and inferCNV estimates. The Portal supports multimodal datasets (CITE-seq, HTO, bulk RNA-seq, spatial) and provides merged project objects without batch correction to facilitate user-driven integration. OpenScPCA curated annotations complement automated labels to better distinguish malignant from normal cells.
Conclusion:
The ScPCA Portal and scpca-nf deliver a modular, openly accessible platform of standardized pediatric tumor single-cell data and tools to speed reproducible discovery and cross-sample comparisons in pediatric cancer research.
Music:
Enjoy the music based on this article at the end of the episode.
Article title:
The Single-Cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors
First author:
Hawkins AG
Journal:
Cell Genomics
DOI:
10.1016/j.xgen.2026.101283
Reference:
Hawkins AG, Shapiro JA, Spielman SJ, et al. The Single-Cell Pediatric Cancer Atlas: Data portal and open-source tools for single-cell transcriptomics of pediatric tumors. Cell Genomics 6, 101283 (2026). https://doi.org/10.1016/j.xgen.2026.101283
License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/
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Episode link: https://basebybase.com/episodes/scpca-data-portal-tools-single-cell-pediatric-cancer
QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-20.
QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited sections include portal overview and dataset scope, data formats and access, SCPCA-nf workflow and quality-control steps, annotation strategy and consensus labeling, CNV inference for malignancy, multimodal data modalities, batch-merging limitations, democratization of access, and future directions.
- transcript topics: Portal scope and dataset size; Data formats and download availability; scpca-nf workflow and quantification; Quality control: empty droplets and miQC; Cell-type annotation and ontology-aware consensus; Copy-number variation inference for malignancy
QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 7
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0
Metadata Audited:
- article_doi
- article_title
- article_journal
- license
Factual Items Audited:
- Portal provides uniformly processed sc/snRNA-seq data and de-identified metadata from pediatric tumor samples
- Portal contains over 700 samples across 55 cancer types; as of May 2026, article reports 704 samples
- Downloads are available as SingleCellExperiment or AnnData objects with QC reports, consensus annotations, and CNV estimates
- scpca-nf uses alevin-fry for fast, memory-efficient quantification; benchmarking shows lower runtime/memory than Cell Ranger
- Quality control includes empty-droplet filtering (DropletUtils) and miQC-based filtering
- Cell-type annotation uses SingleR, CellAssign, and SCimilarity with ontology-aware consensus via the latest common ancestor in Cell Ontology
QC result: Pass.
