SPICEY: an R package for quantifying tissue specificity from single cell multi-omics data
| dc.contributor.author | Fuentes-Páez, Georgina | |
| dc.contributor.author | Molina, Nacho | |
| dc.contributor.author | Ramos-Rodríguez, Mireia | |
| dc.contributor.author | Pasquali, Lorenzo | |
| dc.contributor.funder | Spanish Ministry of Science and Innovation | |
| dc.contributor.funder | Agencia Estatal de Investigación (AEI) | |
| dc.contributor.ror | https://ror.org/02jjdwm75 | |
| dc.date.accessioned | 2026-05-06T16:46:36Z | |
| dc.date.issued | 2026-03-18 | |
| dc.description.abstract | 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 entropybased 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-typespecific 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. | |
| dc.description.peerreviewed | Yes | |
| dc.description.sponsorship | This work was supported by “la Caixa” Foundation, LCF-PR-HR24-00150 and by the Spanish Ministry of Science and Innovation projects PID2020-117099RB-I00, PID2023-151556OB-I00 and CNS2024-154742 under the FPI predoctoral fellowship (PRE2021-098216), funded by MICIU/AEI/https://doi-org.ie.idm.oclc.org/10.13039/501100011033 and, as appropriate, by “ESF Investing in your future”, by “ESF + ” or by “European Union NextGenerationEU/PRTR”. M.R.-R. is supported by the EFSD/Lilly Young Investigator Award. This work was made possible through the “Unidad de Excelencia María de Maeztu” CEX2024-001431-M, funded by MICIU/AEI/https://doi-org.ie.idm.oclc.org/10.13039/501100011033. | |
| dc.description.status | Published | |
| dc.format | application/pdf | |
| dc.identifier.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, 27(1), 80. https://doi-org.ie.idm.oclc.org/10.1186/s12859-026-06418-y | |
| dc.identifier.doi | https://doi.org/10.1186/s12859-026-06418-y | |
| dc.identifier.issn | 1471-2105 | |
| dc.identifier.officialurl | https://link-springer-com.ie.idm.oclc.org/article/10.1186/s12859-026-06418-y?utm_source=getftr&utm_medium=getftr&utm_campaign=getftr_pilot&getft_integrator=scopus | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14417/4320 | |
| dc.issue.number | 80 | |
| dc.journal.title | BMC bioinformatics | |
| dc.language.iso | eng | |
| dc.page.total | 12 | |
| dc.publisher | Springer Nature | |
| dc.relation.entity | IE University | |
| dc.relation.projectid | PID2020-117099RB-I00 | |
| dc.relation.projectid | PID2023-151556OB-I00 | |
| dc.relation.projectid | CNS2024-154742 | |
| dc.relation.projectid | PRE2021-098216 | |
| dc.relation.projectid | CEX2024-001431-M | |
| dc.relation.school | IE School of Science & Technology | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.keywords | Cell-type specificity | |
| dc.subject.keywords | Single-cell gene regulation | |
| dc.subject.keywords | Epigenomics | |
| dc.subject.keywords | Transcriptomics | |
| dc.subject.keywords | R package | |
| dc.subject.ods | ODS 3 - Salud y bienestar | |
| dc.subject.unesco | 23 Química::2302 Bioquímica ::2302.21 Biología molecular | |
| dc.title | SPICEY: an R package for quantifying tissue specificity from single cell multi-omics data | |
| dc.type | info:eu-repo/semantics/article | |
| dc.version.type | info:eu-repo/semantics/publishedVersion | |
| dc.volume.number | 27 | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | d194d8d6-3d87-4ecf-9d6e-f108ec786250 | |
| relation.isAuthorOfPublication.latestForDiscovery | d194d8d6-3d87-4ecf-9d6e-f108ec786250 |
