RunLTMG: RunLTMG

In carter-allen/IRISFGM: Comprehensive Analysis of Gene Interactivity Networks Based on Single-Cell RNA-Seq

Description

We will use Left-truncated Mixture Gaussian distribution to model the regulatory signal of each gene. Parameter, 'Gene_use', decides number of top high variant gene for LTMG modeling, and here we use all genes.

Usage

RunLTMG(object, ...)

.RunLTMG(object, Gene_use = NULL, seed = 123, k = 5)

## S4 method for signature 'IRISFGM'
RunLTMG(object, Gene_use = NULL, seed = 123, k = 5)

Arguments

object	Input IRIS-FGM object
...	other arguments passed to methods
Gene_use	using X numebr of top variant gene. input a number, recommend 2000.
seed	Set seeds for reproducibility
k	Number of components.

Value

it will reture a LTMG signal matrix

Examples

# If you want to explore DEG, we recommend you should use top 2000 highly variant gene. 
## Not run: 
object <- RunLTMG(object,
Gene_use = 2000, 
seed = 123, 
k = 5)

## End(Not run)
# If you want to run bicluster based on LTMG model, we recommend you should use all genes.
## Not run: 
object <- RunLTMG(object,
Gene_use ='all', 
seed = 123, 
k = 5)
## End(Not run)

carter-allen/IRISFGM documentation built on Dec. 31, 2020, 9:54 p.m.