weightStardust: Weighted Stardust

In InfOmics/stardust: Stardust: Improving Spatial Transcriptomics Data Analysis Through Space Aware Modularity Optimization Based Clustering

Weighted Stardust

Description

This function calls Seurat clustering feature, passing a custom distance matrix that integrates both transcriptional similarity and spatial information through a space weight parameter.

Usage

weightStardust(
  countMatrix,
  spotPositions,
  spaceWeight = 1,
  pcaDimensions = 10,
  res = 0.8
)

Arguments

countMatrix,	dataframe with spots id as columns and genes id as rows
spotPositions,	dataframe with x and y spot coordinates as columns and spots id as rows
spaceWeight,	double in [0,1]. Weight for the linear transformation of spot distance 1 means spot distance weight as much as profile distance, 0 means spot distance doesn't contribute at all in the overall distance measure
pcaDimensions,	number of PCA dimension to include in the distance computation
res,	double resolution for Louvain algorithm

Value

Seurat object with cluster identifications for each spot under active.ident slot.

Author(s)

Eva Viesi, eva [dot] viesi [at] univr [dot] it, University of Verona

Simone Avesani, simone [dot] avesani [at] univr [dot] it, University of Verona

Giovanni Motterle, giovanni [dot] motterle [at] univr [dot] it, University of Verona

InfOmics/stardust documentation built on April 28, 2022, 1:16 a.m.