scANANSE: Preprocessed PBMC Single-Cell Multi-Omics Data

Radboud University Nijmegen provides supplementary data for the scANANSE methodology paper, which enables gene regulatory network and motif analysis of single-cell clusters. The repository contains pre-processed Seurat and Scanpy objects derived from 10x Genomics Cell Ranger ARC data for sorted human PBMC and granulocyte cells. These objects are intended for running the scANANSE pipeline to infer transcription factor activity and regulatory networks from combined RNA and ATAC sequencing.

Use Cases

• Benchmarking the scANANSE pipeline for gene regulatory network inference based on pre-processed PBMC data.
• Analyzing transcription factor binding motifs in single-cell clusters using the provided ATAC-seq fragment data.
• Reproducing the analysis from the scANANSE paper using the supplied Rds and h5ad objects.
• Integrating RNA and ATAC modalities from a common cell population for multi-omics studies.

Strengths

• Data is directly linked to a peer-reviewed scientific publication, providing methodological context.
• Includes pre-processed objects in standard formats (Seurat .Rds, Scanpy .h5ad) for immediate analysis.
• Derived from a publicly available, high-quality 10x Genomics Cell Ranger ARC source dataset.

Limitations

• Critical metadata such as row count, column names, and exact dataset size are unknown across all sources.
• The 'Last updated' date is consistently unknown, making freshness impossible to assess.
• The dataset's primary purpose is as supplementary material for a specific tool, limiting its generalizability.

Provenance

Source

J.A. Arts, Radboud University Nijmegen; raw data from 10x Genomics and the NYGC Multimodal Atlas.

Collection Method

Pre-processed from raw 10x Genomics Cell Ranger ARC sequencing data (filtered feature matrix and ATAC fragments).