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 freezes stable matching,
disables feedback, and retains baseline-model samples for posterior
group and directional differential edge selection. Functions assess balance,
record criterion diagnostics, and visualize within-condition and
differential networks.
| Version: |
1.0.6 |
| 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: |
2026-10-14 |
| DOI: |
10.32614/CRAN.package.scNPM (may not be active yet) |
| 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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