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This dataset contains single-cell CITE-Puro-seq data from induced regulatory T cells (iTregs) generated in vitro. The experiment integrates mRNA expression and puromycin-based protein incorporation to capture both transcriptional and translational states at single-cell resolution. Cells were profiled using a modified CITE-seq protocol incorporating puromycin labelling (CITE-Puro-seq) to quantify active translation. The dataset includes raw and normalised gene expression matrices, puromycin incorporation metrics, quality-control metadata, and dimensionality-reduction embeddings. The file includes the following: obs: quality metrics (n_genes, pct_counts_mt, pct_counts_ribo), puromycin signal, phase scores, Leiden clusters, manual annotations var: gene metadata, ribosomal protein assignment, mitochondrial genes, highly variable genes obsm: PCA, UMAP, diffusion map embeddings layers: raw, counts, scaled matrices uns: clustering and plotting parameters, gene ranking statistics Data refer to induced T regulatory cells differentiated ex vivo under cytokine stimulation. The analysis focuses on translational regulation in T cell differentiation and includes comparison between translationally active and inactive subsets.