Perform Hotspot analysis on Vision Object

Perform Hotspot analysis on Vision Object

runHotspot(
  object,
  model = "normal",
  tree = FALSE,
  number_top_genes = 1000,
  num_umi = NULL,
  min_gene_threshold = 20,
  n_neighbors = NULL,
  autocorrelation_fdr = 0.05,
  clustering_fdr = 0.5,
  logdata = FALSE
)

Arguments

object

Vision Object

model

model argument for Hotspot, one of

• normal

• danb

• bernoulli

• none

tree

whether to use tree as latent space. If TRUE, object should have a tree slot.

number_top_genes

Hotspot argument for number of genes to consider

num_umi

optional dataframe containing umi counts in first column for barcodes

min_gene_threshold

minimum number of genes in Hotspot module

n_neighbors

number of neighbors to consider in latent space

autocorrelation_fdr

threshold for significance for genes autocorr

clustering_fdr

threshold for significance for clustering modules

logdata

boolean, log the expression data, avoid for danb Populates the modData, HotspotModuleScores, ModuleSignatureEnrichment and HotspotObject slots of object, as well as recalculates signature scores for new modules.

Value

the modified Vision object