StardustOnSeurat: Stardust on Seurat

In SimoneAvesani/Stardust_rCASC: stardust: Improving Spatial Transcriptomics Data Analysis Through Space Aware Modularity Optimization Based Clustering.

Description

This function calls Seurat clustering feature, passing a custom distance matrix that integrate both transcriptional similarity and spatial information

Usage

StardustOnSeurat(
  countMatrix,
  spotPositions,
  spaceWeight = 1,
  pcaDimensions = 5
)

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.

Value

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

Author(s)

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

SimoneAvesani/Stardust_rCASC documentation built on Dec. 18, 2021, 2:02 p.m.