SpatCluster: Kmeans methods to calculate spatial gene expression pattern

In YeehanXiao/STREAM: STREAM: Spatial Transcriptomics data Analyses and Modeling

Kmeans methods to calculate spatial gene expression pattern

Description

Kmeans methods to calculate spatial gene expression pattern

HmrfCluster

Cluster analysis with spatial single RNA-seq data

Usage

KmeansCluster(
  object,
  cellType = "leiden",
  method = "maximum",
  k = 10,
  centers = 6,
  iter.max = 300,
  nstart = 10,
  ...
)

HmrfCluster(
  object,
  knn = 5,
  expressValue = "scaled",
  spatialGenes = NULL,
  outputFolder = NULL,
  kdomain = 5,
  ...
)

SpatCluster(object, ...)

Arguments

object	An Giotto object
cellType	Column in meta to assign cell-type-annotation for spatial clustering. Default as "leiden" when external annotation is missing.
method	The distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". Any unambiguous substring can be given.
k	Defines k for the k-nearest neighbor algorithm
centers	The number of clusters
iter.max	The maximum number of iterations allowed
nstart	If centers is a number, how many random sets should be chosen
...	Argument passed to other methods
knn	number of nearest neighbors based on physical distance
expressValue	Expression values to use (default [scaled])
spatialGenes	Spatial genes to use for HMRF
outputFolder	Output folder to save results
kdomain	Number of HMRF domains, default 5

Value

giotto object

YeehanXiao/STREAM documentation built on Aug. 13, 2022, 6:43 p.m.