Chapter 4 scRNA-seq
4.1 Load scRNA-seq data
In the tutorial, the scRNA-seq of one APL (AML with PML::RARA fusion, also called acute promyelocytic leukemia)) patient (including 3,000 cells) was used for illustration.
The expample data of APL scRNA-seq can be downloaded via APL scrna demo data
# Library packages
library(Seurat)
library(HematoMap)
# Read count matrix of APL
aml.count <- readRDS("data/AML_scRNA_count.rds")
dim(aml.count)## [1] 36601 3000# Construct Seurat object
aml <- Seurat::CreateSeuratObject(counts = aml.count,
project = "aml",
min.cells = 0,
min.features = 0)## Warning: Data is of class matrix. Coercing to dgCMatrix.## An object of class Seurat
## 36601 features across 3000 samples within 1 assay
## Active assay: RNA (36601 features, 0 variable features)
## 1 layer present: counts4.2 Calculate similarities
aml <- readRDS("data/AML_scRNA_seurat.rds")
# Construct HematoMap object
hmap <- HematoMap::CreateSubclusterObject(aml)## [INFO] 2024-07-22 10:38:20.557213: Subcluster Computing##
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|===========================================================================================================================| 100%, Elapsed 00:06## [INFO] 2024-07-22 10:38:54.000281: CosineDist Running## [INFO] 2024-07-22 10:39:18.238693: CosineDist Complete!## An object of class HematoSubCluster
## 54 sub-clusters with cosine distance# C0:0001 was one of the sub-clusters in hmap
# This plot illustrate the "Like" score between sub-cluster in APL and normal BMMCs
plotThetaLike(hemato.subc = hmap, plot.scell = "C0:0001")
4.3 Visualization
# Visualization for APL (circle tree)
plotCircleTree(hemato.subc = hmap, group.subc = "external", top.subc = 3,
color.mapping = "cell.type", title = "APL BMMCs")
# Visualization for APL (circle tree without population label)
# clean version
plotCircleTree(hemato.subc = hmap, group.subc = "external", top.subc = 3,
color.mapping = "cell.type", title = "APL BMMCs",
label.population = FALSE)
# Visualization for the normal BMMC (the reference) (circle tree)
plotCircleTree(hemato.subc = hmap, group.subc = "reference", top.subc = 3,
color.mapping = "cell.type", title = "Normal BMMCs")
# Visualization for APL (circle tree)
plotCircleTree(hemato.subc = hmap, group.subc = "external", top.subc = 3,
color.mapping = "cell.percentage", title = "APL BMMCs")
# Visualization for the normal BMMC (the reference) (circle tree)
plotCircleTree(hemato.subc = hmap, group.subc = "reference", top.subc = 3,
color.mapping = "cell.percentage", title = "Normal BMMCs")
Visualization using the absolute proportional mode.
# Absolute proportional mode
# Visualization for APL (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "external",
color.mapping = "cell.type", title = "APL BMMCs",
size.mode = "absolute.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)
# Absolute proportional mode
# Visualization for the normal BMMCs (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "reference",
color.mapping = "cell.type", title = "Normal BMMCs",
size.mode = "absolute.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)
# Absolute proportional mode
# Visualization for APL (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "external",
color.mapping = "cell.percentage", title = "APL BMMCs",
size.mode = "absolute.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)
# Absolute proportional mode
# Visualization for the normal BMMCs (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "reference",
color.mapping = "cell.percentage", title = "Normal BMMCs",
size.mode = "absolute.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)
Visualization using the relative proportional mode.
# Relative proportional mode
# Visualization for APL (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "external",
color.mapping = "cell.type", title = "APL BMMCs",
size.mode = "relative.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)
# Relative proportional mode
# Visualization for the normal BMMCs (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "reference",
color.mapping = "cell.type", title = "Normal BMMCs",
size.mode = "relative.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)
# Relative proportional mode
# Visualization for APL (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "external",
color.mapping = "cell.percentage", title = "APL BMMCs",
size.mode = "relative.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)
# Relative proportional mode
# Visualization for the normal BMMCs (hierarchy tree)
plotClusterTree(hemato.subc = hmap, group.subc = "reference",
color.mapping = "cell.percentage", title = "Normal BMMCs",
size.mode = "relative.pct", top.subc = 3,
point.size = 12, label.cell = TRUE)