| scDHA.vis {scDHA} | R Documentation | 
scDHA visulization
Description
Generating 2D embeded data for visulation.
Usage
scDHA.vis(sc = sc, method = "UMAP", ncores = 10L, seed = NULL)
Arguments
| sc | Embedding object produced by the  | 
| method | Visualization method to use. It can be "UMAP" or "scDHA". The default setting is "UMAP". | 
| ncores | Number of processor cores to use. | 
| seed | Seed for reproducibility. | 
Value
a list with the following keys:
- pred - A matrix representing the 2D projection of single-cell data, where rows represent samples and columns represent latent components. 
Examples
library(scDHA)
#Load example data (Goolam dataset)
data('Goolam'); data <- t(Goolam$data); label <- as.character(Goolam$label)
#Log transform the data 
data <- log2(data + 1)
if(torch::torch_is_installed()) #scDHA need libtorch installed
{
  #Generate clustering result, the input matrix has rows as samples and columns as genes
  result <- scDHA(data, ncores = 2, seed = 1)
  #Generate 2D representation, the input is the output from scDHA function
  result <- scDHA.vis(result, ncores = 2, seed = 1)
  #Plot the representation of the dataset, different colors represent different cell types
  plot(result$pred, col=factor(label), xlab = "scDHA1", ylab = "scDHA2")
}
[Package scDHA version 1.2.2 Index]