hippo_dimension_reduction: compute t-SNE or umap of each round of HIPPO

In tk382/HIPPO: Heterogeneity-Induced Pre-Processing tOol

Description

compute t-SNE or umap of each round of HIPPO

Usage

hippo_dimension_reduction(
  sce,
  method = c("umap", "tsne"),
  perplexity = 30,
  featurelevel = 1
)

Arguments

sce	SingleCellExperiment object with hippo object in it.
method	a string that determines the method for dimension reduction: either 'umap' or 'tsne
perplexity	numeric perplexity parameter for Rtsne function
featurelevel	the round of clustering that you will extract features to reduce the dimension

Value

a data frame of dimension reduction result for each k in 1, ..., K

Examples

data(toydata)
set.seed(20200505)
toydata = hippo(toydata,
          feature_method = "zero_inflation",
          clustering_method = "kmeans",
          K = 4,
          outlier_proportion = 0.00001)
toydata = hippo_dimension_reduction(toydata, method="tsne")
hippo_tsne_plot(toydata)

tk382/HIPPO documentation built on Aug. 17, 2021, 2:29 p.m.