plot_heatmap_for_marker_genes: Plot heatmap for identified marker genes

In supatt-lab/SingCellaR: SingCellaR: an integrative analysis tool for single-cell RNA sequencing (scRNA-seq) data

Plot heatmap for identified marker genes

Description

Plot heatmap for identified marker genes

Usage

plot_heatmap_for_marker_genes(
  object,
  cluster.type = c("walktrap", "louvain", "kmeans", "merged_louvain", "merged_walktrap",
    "merged_kmeans"),
  n.TopGenes = 5,
  min.log2FC = 0.5,
  min.expFraction = 0.3,
  isClusterByRow = F,
  col.scaled.min = -2.5,
  col.scaled.max = 2.5,
  col.low = "blue",
  col.mid = "black",
  col.high = "red",
  rowFont.size = 6,
  split.line.col = "white",
  split.line.type = 1,
  split.line.lwd = 1,
  use_raster = FALSE
)

Arguments

object	The SingCellaR object.
cluster.type	The clustering method name.
n.TopGenes	The number of top differential genes. Default 5
min.log2FC	The minimum log2FC cutoff. Default 0.5
min.expFraction	The minimum cutoff for the fraction of expressing cell frequency. Default 0.3
isClusterByRow	is logical. If TRUE, the clustering by row will be performed.
col.scaled.min	The minimum scaled value. Default -2.5
col.scaled.max	The maximum scaled value. Default 2.5
col.low	The low color gradient. Default blue
col.mid	The mid color gradient. Default black
col.high	The high color gradient. Default red
rowFont.size	The row font size. Default 6
split.line.col	The split line color. Default white
split.line.type	The split line type. Default 1
split.line.lwd	The split line lwd. Default 1
use_raster	Whether render the heatmap body as a raster image. It helps to reduce file size when the matrix is huge.

supatt-lab/SingCellaR documentation built on Aug. 24, 2023, 5:49 p.m.