SPICEY: an R package for quantifying tissue specificity from single cell multi-omics data

Background

Single-cell technologies allow detailed mapping of cell type-specific regulatory and transcriptomic landscapes, yet a systematic way to quantify cell type specificity of chromatin accessibility and gene expression remains limited. SPICEY (SPecificity Index for Coding and Epigenetic activitY) is an R package that measures cell-type specificity from single cell multi-omic data.

Results

We developed SPICEY, an R package that combines differential and entropy-based metrics to measure cell-type specificity from annotated single-cell accessibility and gene expression data. It computes two indices: RETSI (Regulatory Element cell Type Specificity Index) for chromatin accessibility and GETSI (Gene Expression cell Type Specificity Index) for gene expression. When links between distal chromatin regions and target genes are provided, SPICEY integrates regulatory and transcriptional specificity scores.

Conclusions

Applied to human pancreatic islet data, SPICEY identified cell-type-specific gene-regulatory pairs and regulatory features enriched in endocrine cells -including beta cells- providing a framework to dissect cell-type-specific regulatory mechanisms in health and disease.

Citation

Fuentes-Páez, G., Molina, N., Ramos-Rodríguez, M., & Pasquali, L. (2026). SPICEY: an R package for quantifying tissue specificity from single cell multi-omics data. BMC bioinformatics.

Authors from IE Research Datalab