SILGGM

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) (2) the de-sparsified nodewise scaled Lasso Jankova and van de Geer (2017) (3) the de-sparsified graphical Lasso Jankova and van de Geer (2015) (4) the GGM estimation with false discovery rate control (FDR) using scaled Lasso or Lasso Liu (2013). Windows users should install 'Rtools' before the installation of this package.

Last 30 days

This package has been downloaded 171 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

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Last 365 days

This package has been downloaded 1,945 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 24 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.