Reconstructing the Regulatory Programs of Target Genes in scRNA-Seq Data
Allocate 3d-array and fill with matrix along first dimension
Extract final configurations into a data frame
Create a table of module overlap for two clusterings
Compute NNLS coefficients
Compute OLS coefficients
Compute ridge regression coefficients
Compute Hubert's and Arabie's Adjusted Rand index
Compute the Rand index
ADMM algorithm for solving the group-penalized least squares problem
Format count table nicely
Fast computation of correlation
Determine module sizes
Get the average number of active regulators per module
Return the number of final configurations
Compute Rand indices
Return list of regulator genes
Extract target gene modules for given penalization parameters
Perform the computations for thresholded Jaccard distance
Compute indicator matrix of pairwise distances smaller than threshold
Determine initial centers for the kmeans++ algorithm
Perform the k-means++ algorithm
Plot average silhouette scores and average predictive
Plotting the regulatory table from scregclust as a directed graph
Plot individual silhouette scores
Quick'n'dirty progress bar
Remove empty modules
Reset input 3d-array by filling matrix along first dimension
Package data before clustering
scregclust: Reconstructing the Regulatory Programs of Target Genes in ...
Uncover gene modules and their regulatory programs from single-cell da...
Split Sample
Implementation of the scregclust algorithm described in Larsson, Held, et al. (2024) <doi:10.1038/s41467-024-53954-3> which reconstructs regulatory programs of target genes in scRNA-seq data. Target genes are clustered into modules and each module is associated with a linear model describing the regulatory program.
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