InteNet: Integrate network data from single-cell RNA-seq and ATAC-seq

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

Integrate network data from single-cell RNA-seq and ATAC-seq

Description

For the SNARE-seq dataset, a droplet-based method to simultaneously profile gene expression and chromatin accessibility in each of thousands of single nuclei, the InteNet function can integrate network data of scRNA-seq data and scATAC-seq data (results of the ConNetGNN function) to into a gene-cell network.

Usage

InteNet(RNA_net, ATAC_net, parallel.cores = 2, verbose = TRUE)

Arguments

RNA_net	Network data for RNA datasets. Produced by the ConNetGNN function.
ATAC_net	Network data for ATAC datasets. Produced by the ConNetGNN function.
parallel.cores	Number of processors to use when doing the calculations in parallel (default: 2). If parallel.cores=0, then it will use all available core processors unless we set this argument with a smaller number.
verbose	Gives information about each step. Default: TRUE.

Details

InteNet

The scATAC-seq dataset needs to be converted into a gene activity matrix according to the process of Signac(https://satijalab.org/signac/articles/snareseq.html). The subsequent process is consistent with the scRNA-seq dataset. The InteNet function then integrates the network data of RNA-seq data and ATAC-seq data into a gene-cell network. With integrated network data as input, scPathway and cpGModule functions will infer pathway activity score matrix and gene modules supported by single-cell multi-omics.

Value

A list.

Examples

require(ActivePathways)
require(parallel)
data(RNA_net)
data(ATAC_net)
## Not run: 
RNA_ATAC_IntNet<-InteNet(RNA_net,ATAC_net,parallel.cores=1)

## End(Not run)

# View data
data(RNA_ATAC_IntNet)
summary(RNA_ATAC_IntNet)

scapGNN documentation built on Aug. 8, 2023, 9:06 a.m.