R: Graph Neural Network-Based Framework for Single Cell Active Pathways and Gene Modules Analysis

# Graph Neural Network-Based Framework for Single Cell Active Pathways and Gene Modules Analysis

## Documentation for package ‘scapGNN’ version 0.1.4

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

.RunLTMG | Run Left-truncated mixed Gaussian
ATAC_net | Results of ConNetGNN() for scATAC-seq data from SNARE-seq dataset
BIC_LTMG | BIC_LTMG
BIC_ZIMG | BIC_ZIMG
ConNetGNN | Construct association networks for gene-gene, cell-cell, and gene-cell based on graph neural network (GNN)
ConNetGNN_data | The results of ConNetGNN() function
cpGModule | Identify cell phenotype activated gene module
create_scapGNN_env | Create the create_scapGNN_env environment on miniconda
Fit_LTMG | Fitting function for Left-truncated mixed Gaussian
Global_Zcut | Global_Zcut
H9_0h_cpGM_data | Cell-activated gene modules under the 0-hour phenotype
H9_24h_cpGM_data | Cell-activated gene modules under the 24-hour phenotype
H9_36h_cpGM_data | Cell-activated gene modules under the 36-hour phenotype
Hv_exp | Single-cell gene expression profiles
instPyModule | Install the pyhton module through the reticulate R package
InteNet | Integrate network data from single-cell RNA-seq and ATAC-seq
isLoaded | The internal functions of the 'scapGNN' package
load_path_data | load pathway or gene set's gmt file
LTMG | Left-truncated mixed Gaussian
LTMG-class | An S4 class to represent the input data for LTMG.
plotCCNetwork | Visualize cell cluster association network graph
plotGANetwork | Visualize gene association network graph of a gene module or pathway at the specified cell phenotype
plotMulPhenGM | Visualize gene association network graph for activated gene modules under multiple cell phenotypes
Preprocessing | Data preprocessing
Pure_CDF | Pure_CDF
RNA_ATAC_IntNet | Results of InteNet() for integrating scRNA-seq and scATAC-seq data.
RNA_net | Results of ConNetGNN() for scRNA-seq data from SNARE-seq dataset
RunLTMG | Run Left-truncated mixed Gaussian
RunLTMG-method | Run Left-truncated mixed Gaussian
RWR | Function that performs a random Walk with restart (RWR) on a given graph
scPathway | Infer pathway activation score matrix at single-cell resolution
scPathway_data | Single cell pathway activity matrix