correlation_heatmap: This function returns a correlation heatmap matrix between...

In Single-Cell-Genomics-Group-CNAG-CRG/SCrafty-package: R package to store useful functions to analyze single-cell data that the entire team can benefit

This function returns a correlation heatmap matrix between the features of interest specified including genes and or metadata features.

Description

This function returns a correlation heatmap matrix between the features of interest specified including genes and or metadata features.

Usage

correlation_heatmap(
  se,
  genes = NULL,
  feats = NULL,
  assay = "Spatial",
  slot = "data",
  cor_method = "pearson",
  ...
)

Arguments

se	Spatial Seurat object we want to assess.
genes	vector with genes that we want to build the correlation heatmap with.
feats	vector with metadata features that we want to build the correlation heatmap with.
assay	assay from where we want to extract the gene expression.
slot	slot from where we want to extract the gene expression.
cor_method	Method to use for correlation: c("pearson", "kendall", "spearman"). By default pearson.
...	Further arguments to pass to ggcorrplot::ggcorrplot

Value

Correlation matrix heatmap

Examples

## Not run: 
library(Seurat)
library(SeuratData)
sp_obj <- SeuratData::LoadData(ds = "stxBrain", type = "posterior1")
correlation_heatmap(
  se = sp_obj,
  slot = "counts",
  assay = "Spatial",
  genes = c("Ms4a1", "Cd79a", "Cd3d", "Cd3e", "Cd8a"),
  feats = NULL,
  cor_method = "pearson",
  title = "Gene-Gene correlation heatmap")

## End(Not run)

Single-Cell-Genomics-Group-CNAG-CRG/SCrafty-package documentation built on Aug. 20, 2022, 9:29 a.m.