runUMAP: Run UMAP

In sqjin/CellChat: Inference and analysis of cell-cell communication from single-cell and spatial transcriptomics data

Run UMAP

Description

Run UMAP

Usage

runUMAP(
  data.use,
  n_neighbors = 30L,
  n_components = 2L,
  metric = "correlation",
  n_epochs = NULL,
  learning_rate = 1,
  min_dist = 0.3,
  spread = 1,
  set_op_mix_ratio = 1,
  local_connectivity = 1L,
  repulsion_strength = 1,
  negative_sample_rate = 5,
  a = NULL,
  b = NULL,
  seed.use = 42L,
  metric_kwds = NULL,
  angular_rp_forest = FALSE,
  verbose = FALSE
)

Arguments

data.use	input data matrix
n_neighbors	This determines the number of neighboring points used in local approximations of manifold structure. Larger values will result in more global structure being preserved at the loss of detailed local structure. In general this parameter should often be in the range 5 to 50.
n_components	The dimension of the space to embed into.
metric	This determines the choice of metric used to measure distance in the input space.
n_epochs	the number of training epochs to be used in optimizing the low dimensional embedding. Larger values result in more accurate embeddings. If NULL is specified, a value will be selected based on the size of the input dataset (200 for large datasets, 500 for small).
learning_rate	The initial learning rate for the embedding optimization.
min_dist	This controls how tightly the embedding is allowed compress points together. Larger values ensure embedded points are moreevenly distributed, while smaller values allow the algorithm to optimise more accurately with regard to local structure. Sensible values are in the range 0.001 to 0.5.
spread	he effective scale of embedded points. In combination with min.dist this determines how clustered/clumped the embedded points are.
set_op_mix_ratio	Interpolate between (fuzzy) union and intersection as the set operation used to combine local fuzzy simplicial sets to obtain a global fuzzy simplicial sets.
local_connectivity	The local connectivity required - i.e. the number of nearest neighbors that should be assumed to be connected at a local level. The higher this value the more connected the manifold becomes locally. In practice this should be not more than the local intrinsic dimension of the manifold.
repulsion_strength	Weighting applied to negative samples in low dimensional embedding optimization. Values higher than one will result in greater weight being given to negative samples.
negative_sample_rate	The number of negative samples to select per positive sample in the optimization process. Increasing this value will result in greater repulsive force being applied, greater optimization cost, but slightly more accuracy.
a	More specific parameters controlling the embedding. If NULL, these values are set automatically as determined by min. dist and spread.
b	More specific parameters controlling the embedding. If NULL, these values are set automatically as determined by min. dist and spread.
seed.use	Set a random seed. By default, sets the seed to 42.
metric_kwds, angular_rp_forest, verbose	other parameters used in UMAP

sqjin/CellChat documentation built on Nov. 10, 2023, 4:29 a.m.