SILGGM
Statistical Inference of Large-Scale Gaussian Graphical Model in Gene Networks
Provides a general framework to perform statistical inference of each gene pair and global inference of whole-scale gene pairs in gene networks using the well known Gaussian graphical model (GGM) in a time-efficient manner. We focus on the high-dimensional settings where p (the number of genes) is allowed to be far larger than n (the number of subjects). Four main approaches are supported in this package: (1) the bivariate nodewise scaled Lasso (Ren et al (2015) <doi:10.1214/14-AOS1286>) (2) the de-sparsified nodewise scaled Lasso (Jankova and van de Geer (2017) <doi:10.1007/s11749-016-0503-5>) (3) the de-sparsified graphical Lasso (Jankova and van de Geer (2015) <doi:10.1214/15-EJS1031>) (4) the GGM estimation with false discovery rate control (FDR) using scaled Lasso or Lasso (Liu (2013) <doi:10.1214/13-AOS1169>). Windows users should install 'Rtools' before the installation of this package.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | SILGGM_1.0.0.tar.gz |
126.3 KiB |
1.0.0 |
rolling linux/noble R-4.5 | SILGGM_1.0.0.tar.gz |
127.8 KiB |
1.0.0 |
rolling source/ R- | SILGGM_1.0.0.tar.gz |
15.9 KiB |
1.0.0 |
latest linux/jammy R-4.5 | SILGGM_1.0.0.tar.gz |
126.3 KiB |
1.0.0 |
latest linux/noble R-4.5 | SILGGM_1.0.0.tar.gz |
127.8 KiB |
1.0.0 |
latest source/ R- | SILGGM_1.0.0.tar.gz |
15.9 KiB |
1.0.0 |
2026-04-26 source/ R- | SILGGM_1.0.0.tar.gz |
15.9 KiB |
1.0.0 |
2026-04-23 source/ R- | SILGGM_1.0.0.tar.gz |
15.9 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | SILGGM_1.0.0.zip |
442.6 KiB |
1.0.0 |
2025-04-20 source/ R- | SILGGM_1.0.0.tar.gz |
15.9 KiB |