nf_xpatial: A Reproducible Framework for Standardized Preprocessing and Clustering of Xenium Data
Year: 2026
Type: preprint
Abstract: ABSTRACT Recent advances in spatial transcriptomics have enabled the profiling of increasingly larger numbers of genes while retaining single-cell and subcellular resolution in situ . However, standardized bioinformatics workflows for analyzing these datasets have lagged behind, with existing pipelines focusing primarily on image processing and cell segmentation. To address this gap, we present nf_xpatial, a best-practices Nextflow pipeline for the downstream analysis of 10x Genomics Xenium data. The pipeline performs quality control, filtering, log and cell area normalization, multi-sample integration, and both expression-driven and spatially informed clustering across systematic parameter sweeps, allowing users to evaluate and compare clustering resolutions and spatial modeling parameters within a single reproducible run. Overall, nf_xpatial streamlines the processing of Xenium data from platform outputs to integrated single-cell and spatial clustering datasets, providing a standardized starting point from which biologists can finetune parameters and proceed to hypothesis-driven spatial analyses. Availability and implementation The source code and detailed documentation are freely available at https://github.com/U-BDS/nf_xpatial under the GPL-3 license. SUPPLEMENTARY INFORMATION Supplementary data is provided.
Institution: University of Alabama at Birmingham
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Funder: Civitan International
OpenAlex ID: W7204708048
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