scPairs: Identifying Synergistic Gene Pairs in Single-Cell and Spatial
Transcriptomics
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>.
| Version: |
0.1.8 |
| 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) |
| Published: |
2026-03-05 |
| DOI: |
10.32614/CRAN.package.scPairs (may not be active yet) |
| Author: |
Zhaoqing Wang 
[aut, cre] |
| Maintainer: |
Zhaoqing Wang <zhaoqingwang at mail.sdu.edu.cn> |
| BugReports: |
https://github.com/zhaoqing-wang/scPairs/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/zhaoqing-wang/scPairs |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
scPairs results |
Documentation:
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