Identifying Synergistic Gene Pairs in Single-Cell and Spatial Transcriptomics R package scPairs version 0.1.8 Discovers synergistic gene pairs in single-cell RNA-seq and spatial transcriptomics data. Unlike conventional pairwise co-expression analyses that rely on a single correlation metric, scPairs integrates 14 complementary metrics across five orthogonal evidence layers to compute a composite synergy score with optional permutation-based significance testing. The five evidence layers span cell-level co-expression (Pearson, Spearman, biweight midcorrelation, mutual information, ratio consistency), neighbourhood-aware smoothing (KNN-smoothed correlation, neighbourhood co-expression, cluster pseudo-bulk, cross-cell-type, neighbourhood synergy), prior biological knowledge (GO/KEGG co-annotation Jaccard, pathway bridge score), trans-cellular interaction, and spatial co-variation (Lee's L, co-location quotient). This multi-scale design enables researchers to move beyond simple co-expression towards a comprehensive characterisation of cooperative gene regulation at transcriptomic and spatial resolution. For more information, see the package documentation at <https://github.com/zhaoqing-wang/scPairs>. Software Depends: R (>= 4.1.0) Imports: data.table, ggplot2, ggraph, ggrepel, igraph, methods, Matrix, patchwork, Seurat (>= 4.0), SeuratObject, stats, tidygraph, tidyr Suggests: AnnotationDbi, org.Mm.eg.db, org.Hs.eg.db, crayon, ggExtra, RANN, testthat (>= 3.0.0) Zhaoqing Wang <zhaoqingwang@mail.sdu.edu.cn> Comprehensive R Archive Network (CRAN) Zhaoqing Wang [aut, cre] (ORCID: <https://orcid.org/0000-0001-8348-7245>) MIT + file LICENSE (https://CRAN.R-project.org/package=scPairs/LICENSE) 2026-03-05 application/tgz https://CRAN.R-project.org/package=scPairs doi:10.32614/CRAN.package.scPairs