autoStardust: Automatic Stardust

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

Automatic Stardust

Description

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

Usage

autoStardust(countMatrix, spotPositions, 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
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.