scNPM: Single-Cell Network Propensity Matching
Estimates and compares heterogeneous gene conditional-dependence
networks from single-cell expression data. A latent Gaussian mixture and
probit observation mechanism represent cellular heterogeneity and zero
observations. Protein interaction information supplies edge-specific prior
weights, while network propensity matching links cell clusters across
conditions and guides adaptation. Staged inference fixes correspondence after adaptation,
disables adaptation feedback, and jointly models matched network edges with
a four-state spike-and-slab prior for posterior group and directional
differential edge selection. Functions assess balance,
record criterion diagnostics, and visualize within-condition and
differential networks.
| Version: |
1.1.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
Rcpp (≥ 1.0.10), Matrix, igraph (≥ 1.3.0), ggplot2 (≥
3.3.0), ggrepel (≥ 0.9.0), scales (≥ 1.2.0), stats, utils, tools |
| LinkingTo: |
Rcpp, RcppArmadillo (≥ 0.12.6.4.0), RcppParallel (≥ 5.1.7) |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2026-10-19 |
| DOI: |
10.32614/CRAN.package.scNPM |
| Author: |
Tao Liu [aut, cre] |
| Maintainer: |
Tao Liu <25210690190 at m.fudan.edu.cn> |
| BugReports: |
https://github.com/taostat1/scNPM_R_package/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/taostat1/scNPM_R_package |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++17, OpenMP |
| Materials: |
README, NEWS |
| CRAN checks: |
scNPM results |
Documentation:
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