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

View source: R/plotting.R

Gene.gene.corheatmapR Documentation

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.