Single-cell spatial (scs) omics: Recent developments in data analysis Camacho Páez, José Sorochan Armstrong, Michael García Martínez, María Luz Díaz, Caridad Gómez Llorente, Carolina Single-cell Spatial Omics Data Analysis Computational This work was supported by grant no. PID2023-1523010B-IOO (MuSTARD), funded by the Agencia Estatal de Investigación in Spain, call no. MICIU/AEI/10.13039/501100011033, and by the European Regional Development Fund. Michael Sorochan Armstrong was funded through the MSCA program, project: MAHOD-101106986. Over the past few years, technological advances have allowed for measurement of omics data at the cell level, creating a new type of data generally referred to as single-cell (sc) omics. On the other hand, the so-called spatial omics are a family of techniques that generate biological information in a spatial domain, for instance, in the volume of a tissue. In this survey, we are mostly interested in the intersection between sc and spatial (scs) omics and in the challenges and opportunities that this new type of data pose for downstream data analysis methodologies. Our goal is to cover all major omics modalities, including transcriptomics, genomics, epigenomics, proteomics and metabolomics. 2025-02-18T08:41:30Z 2025-02-18T08:41:30Z 2025 journal article Published version: Camacho Páez, José et al. TrAC Trends in Analytical Chemistry Volume 183, February 2025, 118109. https://doi.org/10.1016/j.trac.2024.118109 https://hdl.handle.net/10481/102443 10.1016/j.trac.2024.118109 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elsevier