Package: SPICEY 1.3.0

Georgina Fuentes-Páez

SPICEY: Calculates cell type specificity from single cell data

SPICEY (SPecificity Index for Coding and Epigenetic activitY) is an R package designed to quantify cell-type specificity in single-cell transcriptomic and epigenomic data, particularly scRNA-seq and scATAC-seq. It introduces two complementary indices: the Gene Expression Tissue Specificity Index (GETSI) and the Regulatory Element Tissue Specificity Index (RETSI), both based on entropy to provide continuous, interpretable measures of specificity. By integrating gene expression and chromatin accessibility, SPICEY enables standardized analysis of cell-type-specific regulatory programs across diverse tissues and conditions.

Authors:Georgina Fuentes-Páez [aut, cre], Nacho Molina [aut], Mireia Ramos-Rodriguez [aut], Lorenzo Pasquali [aut], Ministerio de Ciencia e Innovación Spain [fnd]

SPICEY_1.3.0.tar.gz
SPICEY_1.3.0.zip(r-4.7)SPICEY_1.3.0.zip(r-4.6)SPICEY_1.3.0.zip(r-4.5)
SPICEY_1.3.0.tgz(r-4.6-any)SPICEY_1.3.0.tgz(r-4.5-any)
SPICEY_1.3.0.tar.gz(r-4.7-any)SPICEY_1.3.0.tar.gz(r-4.6-any)
SPICEY_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SPICEY/json (API)

# Install 'SPICEY' in R:

install.packages('SPICEY', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/georginafp/spicey/issues

Datasets:

atac - Example single-cell ATAC-seq differential accessibility data
cicero_links - Example Cicero co-accessibility links
rna - Example single-cell RNA-seq differential expression data

On BioConductor:SPICEY-1.3.0(bioc 3.24)SPICEY-1.2.0(bioc 3.23)

transcriptomics epigenetics singlecell differentialexpression differentialpeakcalling generegulation genetarget geneexpression transcription

4.88 score 1 stars 3 scripts 209 downloads 4 exports 90 dependencies

Last updated from:8c65e8a22d. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	222
linux-devel-x86_64	OK	334
source / vignettes	OK	291
linux-release-x86_64	OK	361
macos-release-arm64	OK	182
macos-oldrel-arm64	OK	201
windows-devel	OK	247
windows-release	OK	227
windows-oldrel	OK	220
wasm-release	OK	206

Exports:annotate_with_coaccessibility annotate_with_nearest SPICEY spicey_heatmap

Dependencies:abind AnnotationDbi askpass BH Biobase BiocBaseUtils BiocGenerics BiocIO BiocParallel Biostrings bit bit64 bitops blob cachem cigarillo cli codetools cowplot cpp11 crayon curl DBI DelayedArray dplyr farver fastmap formatR futile.logger futile.options generics GenomeInfoDb GenomicAlignments GenomicFeatures GenomicRanges ggplot2 glue gtable httr IRanges isoband jsonlite KEGGREST labeling lambda.r lattice lifecycle magrittr Matrix MatrixGenerics matrixStats memoise mime openssl pillar pkgconfig png purrr R6 RColorBrewer RCurl restfulr Rhtslib rjson rlang Rsamtools RSQLite rtracklayer S4Arrays S4Vectors S7 scales Seqinfo snow SparseArray stringi stringr SummarizedExperiment sys tibble tidyr tidyselect UCSC.utils utf8 vctrs viridisLite withr XML XVector yaml

Measuring tissue specificity from single cell data with SPICEY

Rendered fromSPICEY.Rmdusingknitr::rmarkdown

Last update: 2025-10-08
Started: 2025-06-03

Help page	Topics
Add TSS annotation to peaks	.add_tss_annotation
Parses input data of various types (e.g., named lists of 'GRanges' or 'data.frame', or a 'GRangesList') into a single tidy 'data.frame', with a 'cell_type' column.	.parse_input_diff
Standardizes peak input, ensuring that input peaks is a 'GRanges' object, removes alternate scaffolds ('_alt', 'random', 'fix', 'Un'), and assigns region IDs as names.	.standardize_peaks
Annotate peaks with co-accessible genes using Cicero links	annotate_with_coaccessibility
Annotates regulatory elements (e.g., ATAC-seq peaks) to the nearest gene	annotate_with_nearest
Example single-cell ATAC-seq differential accessibility data	atac
Example Cicero co-accessibility links	cicero_links
Compute cell type specificity scores from single-cell RNA and/or ATAC data	compute_spicey_index
Calculate normalized Shannon-entropy of specificity scores	entropy_index
Overlap peaks with gene promoters to obtain gene annotations	extract_gene_peak_annotations
Extract promoter regions annotated gene symbols from a TxDb and AnnotationDbi object	get_promoters
Link RETSI regions to GETSI scores using gene-based association methods	link_spicey
Plot a SPICEY score gene-by-cell-type heatmap	plot_heatmap
Prepare data for SPICEY heatmap	prepare_heatmap_data
Example single-cell RNA-seq differential expression data	rna
Calculate specificity scores for grouped features	specificity_index
SPICEY: Tissue specificity analysis for single-cell data The SPICEY package provides a user-friendly pipeline for quantifying and visualizing tissue specificity specificity from single-cell ATAC-seq and/or single cell RNA-seq datasets, typically processed with tools such as Seurat or Signac. The core outputs of SPICEY are two tissue specific metrics, combined with entropy-based measures.	SPICEY
SPICEY heatmap for gene specificity across cell types	spicey_heatmap

Package: SPICEY 1.3.0

SPICEY: Calculates cell type specificity from single cell data

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