RunDimensionReduction: RunDimensionReduction

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

Description

This function is based on the Seurat package to perform dimension reduction. The input matirx is the LTMG signaling matrix.

Usage

RunDimensionReduction(object, ...)

.runDimensionReduction(
  object,
  mat.source = c("LTMG", "UMImatrix"),
  reduction = "umap",
  dims = 1:15,
  perplexity = 15,
  seed = 1
)

## S4 method for signature 'IRISFGM'
RunDimensionReduction(
  object,
  mat.source = c("LTMG", "UMImatrix"),
  reduction = "umap",
  dims = 1:15,
  perplexity = 15,
  seed = 1
)

Arguments

object	Input IRIS-FGM object.
...	other arguments passed to methods
mat.source	choose source data for running this function either from LTMG signal matrix or from processed data. Values of this parameter are 'LTMG' and 'UMImatrix'
reduction	select a method for dimension reduction, including umap, tsne, and pca.
dims	select the number of PCs from PCA results to perform the following dimension reduction and cell clustering.
perplexity	Perplexity parameter as optimal number of neighbors.
seed	Set the seed of R‘s random number generator, which is useful for creating simulations or random objects that can be reproduced.

Value

This function will generate pca, tsne, or umap dimension reduction results.

Examples

## Not run: 
obejct <- RunDimensionReduction(object,
   mat.source= 'LTMG',
   reduction = 'umap', 
   dims = 1:15 ,
   perplexity = 15, 
   seed = 1)
   
## End(Not run)

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