Gene.gene.corheatmap: heatmap for gene-gene correlation matrix

In GrigoriiNos/rimmi.rnaseq: Set of functions for genomics data analysis

heatmap for gene-gene correlation matrix

Description

This function allows you to plot a heatmap for gene-gene correlation

Usage

Gene.gene.corheatmap(
  Seurat_obj,
  cor.method = "spearman",
  coef.cut.off = 0.3,
  gene.cut.off = 1,
  use.hvg = F,
  imputed = F,
  impute_after = T,
  gene.names = T
)

Arguments

Seurat_obj	Seurat object
cor.method	method to par ro cor function for correlation calculation, spearman is by default, bayesian (package psycho), pearson and kendall can also be used
coef.cut.off	what monimum correlation coeffitient to choose to cut off the noise
gene.cut.off	how much genes should have this correlation coefficient
imputed	should MAGIC imputation be used on an expression matrix primarily to correlation analysis, FALSE by default
impute_after	do you want to impute cor matrix that was generated after analysing unimputed data?
gene.names	do you want do show gene names? Set to FALSE is you gonna have a large matrix

Value

a heaatmap

Examples

Gene.gene.corheatmap(Seurat_obj, do.cluster = T)

GrigoriiNos/rimmi.rnaseq documentation built on April 29, 2022, 5:18 p.m.