A small simulated dataset representing post-analysis scRNA-seq data, suitable
for demonstrating the prepare_from_seurat workflow. Generated
using simulate_cellCounts_fromTissue with 6 cell types, 12
samples (6 control, 6 treated), and ~1500 cells total. Two cell types
(B_cells and Monocytes) have differential abundance between groups.
Format
A list with two elements:
- counts_matrix
A sparse gene-by-cell matrix (50 genes x ~1500 cells) of class
dgCMatrix, suitable forSeuratObject::CreateSeuratObject().- cell_metadata
A data frame with one row per cell and three columns:
- cell_type
Character. Cell type label (one of B_cells, T_cells_CD4, T_cells_CD8, Monocytes, NK_cells, Dendritic_cells).
- sample_id
Character. Sample identifier (sample_1 through sample_12).
- group
Character. Experimental group ("control" or "treated").
Row names are cell barcodes (cell_1, cell_2, ...).