2025-03-20
- Today you have to create a Rmarkdown report. Make it nice:
- Remember that
setwd()is not working in rmarkdown but rmarkdown set as default the folder in which it is, so, if you need to take data from other folders put the entire path - For each point of the exercise put the text of the exercise
- Make at least 1 chunck of code for each exercise (you can do more than one if you think it’s more easy to understand)
- Manipulate figure dimensions to make them visible or change figure parameters
- Import in R all the datasets:
Spatial_expression_data.rdsfile inDatasets: it contains normalized gene expression values for genes annotated in kegg pathways. (load in in theexprobject)Spatial_expression_annotation_genes.csv: it contains information about marker genes for clusters of spots. (load in in themarkobject)Spatial_expression_annotation_pathways.rds: it contains gene annotations (pathway they belong to). (load in in thepathobject)Spatial_expression_annotation_clusters.rds: it contains information about spot division in clusters. (load in in theclusobject)
Remember: you have to take every information and manipulate data only using r functions. Make your code reproducible
options(stringsAsFactors = F)
expr=readRDS("Datasets/Spatial_expression_data.rds")
mark=read.csv("Datasets/Spatial_expression_annotation_genes.csv")
path=readRDS("Datasets/Spatial_expression_annotation_pathways.rds")
clus=readRDS("Datasets/Spatial_expression_annotation_clusters.rds")- Create a subset of
exprby keeping:
- only genes that are at least markers for three clusters in
mark(you can explore functionalities ofrowSums()function) - spots in
clusbelonging to annotated clusters (the ones for with markers are available inmark).
Then:
- make complex heatmap plotting genes on rows and spots on columns. Change color scale to make it meaningful.
library(ComplexHeatmap)
library(grid)
library(circlize)
mark$N_mark=rowSums(mark[, c(2:ncol(mark))])
selected_genes=subset(mark,N_mark>=3)$gene
expr2=subset(expr, rownames(expr)%in%selected_genes)
available_mark=gsub("marker_cluster", "", colnames(mark[2:(ncol(mark)-1)]))
available_mark## [1] "0" "1" "2" "3" "4" "5" "6" "7" "8"spots=subset(clus, cluster%in%available_mark)
head(spots)## cluster spot
## AAACAAGTATCTCCCA-1 4 AAACAAGTATCTCCCA-1
## AAACACCAATAACTGC-1 3 AAACACCAATAACTGC-1
## AAACAGAGCGACTCCT-1 0 AAACAGAGCGACTCCT-1
## AAACAGCTTTCAGAAG-1 7 AAACAGCTTTCAGAAG-1
## AAACAGGGTCTATATT-1 3 AAACAGGGTCTATATT-1
## AAACATTTCCCGGATT-1 1 AAACATTTCCCGGATT-1table(spots$spot%in%colnames(expr2)) # control if all spots are in the expression data frame##
## FALSE TRUE
## 3642 88expr2=expr2[, which(colnames(expr2)%in%spots$spot)]
dim(expr2)## [1] 203 88expr2=as.matrix(expr2)
color=colorRamp2(c(min(unlist(expr2)), mean(unlist(expr2)), max(unlist(expr2))), c("white", "magenta", "purple"))Heatmap(expr2, col=color)
- Add information to the heatmap you created.
Add annotations on both rows (pathway annotation) and columns (spot clusters).
Split columns according to clusters.
Add a barplot annotation on rows showing for each gene the total number of genes that belong to the pathway it belongs to (according to the entire kegg annotation).
p=as.data.frame(table(path$kegg_pathway))
path$N_total=p$Freq[match(path$kegg_pathway, p$Var1)]
expr2_annot=path[match(rownames(expr2), path$gene), c("kegg_pathway", "N_total")]
head(expr2_annot)## kegg_pathway N_total
## GABRD NEUROACTIVE_LIGAND_RECEPTOR_INTERACTION 124
## PRKCZ CHEMOKINE_SIGNALING_PATHWAY 98
## PEX10 PEROXISOME 37
## PANK4 PANTOTHENATE_AND_COA_BIOSYNTHESIS 11
## HES5 NOTCH_SIGNALING_PATHWAY 25
## TNFRSF14 CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION 113ann_sp=spots$cluster[match(colnames(expr2), spots$spot)]
haR = HeatmapAnnotation(
N_g = anno_barplot(expr2_annot$N_total), # annotation name and values
pathway = expr2_annot$kegg_pathway,# other annotation name and values
gp = gpar(col = "black"),
which = "row"
)
haC = HeatmapAnnotation(
cluster = ann_sp,
gp = gpar(col = "black"),
which = "column"
)
color=colorRamp2(c(min(unlist(expr2)), mean(unlist(expr2)), max(unlist(expr2))), c("white", "magenta", "purple"))
ht=Heatmap(expr2, col=color, column_split = ann_sp, left_annotation =haR,
top_annotation = haC)draw(ht, heatmap_legend_side = "bottom",
annotation_legend_side = "bottom")
- Use
Spatial_expression_annotation_genes.csvin Datasets (you already read it).
- Compare markers for cluster 0 ,1 and 3 using a venn diagram. You can try to add colors and to change labels.
- Select the genes that are in common between all the three clusters and make a boxplot for each gene (use facet) to see if there are differences in expression values between the three clusters.
library(VennDiagram)
group1 <- mark$gene[which(mark$marker_cluster0)]
group2 <- mark$gene[which(mark$marker_cluster1)]
group3 <- mark$gene[which(mark$marker_cluster3)]
venn.diagram(
x = list(group1, group2, group3),
category.names = c("Cluster 0" , "Cluster 1" , "Cluster 3"),
filename = "venn_diagram_markers.png",imagetype = "png", # possible imege types are: "png", "tiff" or "svg"
output=TRUE
) ## [1] 1
g=group1[which(group1%in%group2 & group1%in%group3)]
expr_g=expr[g,]
head(expr_g)## AAACAAGTATCTCCCA-1 AAACACCAATAACTGC-1 AAACAGAGCGACTCCT-1
## CHRM3 0.000000 0.0000000 0.000000
## FMN2 0.000000 0.0000000 0.000000
## FH 0.000000 0.6931472 0.000000
## KMO 0.000000 0.0000000 0.000000
## EXO1 0.000000 0.0000000 0.000000
## AKT3 1.609438 0.6931472 1.098612
## AAACAGCTTTCAGAAG-1 AAACAGGGTCTATATT-1 AAACATTTCCCGGATT-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 0.000000 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.609438 1.098612
## AAACCACTACACAGAT-1 AAACCCGAACGAAATC-1 AAACCGGAAATGTTAA-1
## CHRM3 0.000000 0 0.0000000
## FMN2 0.000000 0 0.0000000
## FH 0.000000 0 1.0986123
## KMO 0.000000 0 0.0000000
## EXO1 0.000000 0 0.0000000
## AKT3 1.791759 0 0.6931472
## AAACCGGGTAGGTACC-1 AAACCGTTCGTCCAGG-1 AAACCTAAGCAGCCGG-1
## CHRM3 0.0000000 0.000000 0.0000000
## FMN2 0.0000000 0.000000 0.0000000
## FH 0.6931472 0.000000 0.0000000
## KMO 0.0000000 0.000000 0.0000000
## EXO1 0.0000000 0.000000 0.0000000
## AKT3 2.0794415 1.386294 0.6931472
## AAACCTCATGAAGTTG-1 AAACGAAGAACATACC-1 AAACGACAGTCTTGCC-1
## CHRM3 0.000000 0.0000000 0.0000000
## FMN2 0.000000 0.0000000 0.0000000
## FH 1.098612 0.6931472 0.0000000
## KMO 0.000000 0.0000000 0.0000000
## EXO1 0.000000 0.0000000 0.0000000
## AKT3 1.098612 1.0986123 0.6931472
## AAACGAGACGGTTGAT-1 AAACGCCCGAGATCGG-1 AAACGCTGGGCACGAC-1
## CHRM3 0.0000000 0.0000000 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.0000000 0.6931472 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 0.6931472 1.0986123 1.386294
## AAACGGGCGTACGGGT-1 AAACGGTTGCGAACTG-1 AAACGTGTTCGCCCTA-1
## CHRM3 0.000000 0.000000 0.0000000
## FMN2 0.000000 0.000000 0.0000000
## FH 0.000000 0.000000 0.6931472
## KMO 0.000000 0.000000 0.0000000
## EXO1 0.000000 0.000000 0.0000000
## AKT3 1.386294 1.386294 1.0986123
## AAACTAACGTGGCGAC-1 AAACTCGGTTCGCAAT-1 AAACTCGTGATATAAG-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.0000000 0.0000000 0.0000000
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 0.6931472 0.6931472 0.6931472
## AAACTGCTGGCTCCAA-1 AAACTTAATTGCACGC-1 AAACTTGCAAACGTAT-1
## CHRM3 0 0.000000 0.000000
## FMN2 0 0.000000 0.000000
## FH 0 0.000000 1.098612
## KMO 0 0.000000 0.000000
## EXO1 0 0.000000 0.000000
## AKT3 0 1.386294 0.000000
## AAAGAATGTGGACTAA-1 AAAGACATGAAGTTTA-1 AAAGACCCAAGTCGCG-1
## CHRM3 0.000000 0.000000 0.000000
## FMN2 0.000000 0.000000 0.000000
## FH 0.000000 0.000000 0.000000
## KMO 0.000000 0.000000 0.000000
## EXO1 0.000000 0.000000 0.000000
## AKT3 1.386294 1.386294 1.386294
## AAAGACTGGGCGCTTT-1 AAAGCTTGCCTACATA-1 AAAGGCCCTATAATAC-1
## CHRM3 0.000000 0.000000 0.0000000
## FMN2 0.000000 0.000000 0.0000000
## FH 0.000000 0.000000 0.0000000
## KMO 0.000000 0.000000 0.0000000
## EXO1 0.000000 0.000000 0.0000000
## AKT3 1.386294 1.386294 0.6931472
## AAAGGCTACGGACCAT-1 AAAGGCTCTCGCGCCG-1 AAAGGGATGTAGCAAG-1
## CHRM3 0.000000 0.000000 0.0000000
## FMN2 0.000000 0.000000 0.0000000
## FH 0.000000 1.098612 0.6931472
## KMO 0.000000 0.000000 0.0000000
## EXO1 0.000000 0.000000 0.0000000
## AKT3 1.098612 1.098612 1.3862944
## AAAGGGCAGCTTGAAT-1 AAAGGTAAGCTGTACC-1 AAAGGTCAACGACATG-1
## CHRM3 0.0000000 0.0000000 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.6931472 1.0986123 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 1.3862944 0.6931472 1.098612
## AAAGTAGCATTGCTCA-1 AAAGTCACTGATGTAA-1 AAAGTCGACCCTCAGT-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.6931472 0.6931472 0.6931472
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 0.6931472 1.0986123 0.6931472
## AAAGTGCCATCAATTA-1 AAAGTGTGATTTATCT-1 AAAGTTGACTCCCGTA-1
## CHRM3 0.000000 0 0.0000000
## FMN2 0.000000 0 0.0000000
## FH 0.000000 0 0.6931472
## KMO 0.000000 0 0.0000000
## EXO1 0.000000 0 0.0000000
## AKT3 1.386294 0 1.9459101
## AAATAACCATACGGGA-1 AAATAAGGTAGTGCCC-1 AAATACCTATAAGCAT-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.6931472 0.6931472 0.0000000
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 1.3862944 1.3862944 0.6931472
## AAATAGCTTAGACTTT-1 AAATCACTCCTAAACG-1 AAATCCGATACACGCC-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.6931472 0.6931472 0.0000000
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 1.6094379 1.3862944 0.6931472
## AAATCTAGCCCTGCTA-1 AAATCTGCCCGCGTCC-1 AAATGATTCGATCAGC-1
## CHRM3 0 0.0000000 0.000000
## FMN2 0 0.0000000 0.000000
## FH 0 0.0000000 1.386294
## KMO 0 0.0000000 0.000000
## EXO1 0 0.0000000 0.000000
## AKT3 0 0.6931472 1.098612
## AAATGCTCGTTACGTT-1 AAATGGCATGTCTTGT-1 AAATGGCCCGTGCCCT-1
## CHRM3 0.000000 0 0.0000000
## FMN2 0.000000 0 0.0000000
## FH 0.000000 0 0.0000000
## KMO 0.000000 0 0.0000000
## EXO1 0.000000 0 0.0000000
## AKT3 1.098612 0 0.6931472
## AAATGGTCAATGTGCC-1 AAATGTATCTTATCCC-1 AAATTAACGGGTAGCT-1
## CHRM3 0.0000000 0.000000 0.0000000
## FMN2 0.0000000 0.000000 0.0000000
## FH 0.6931472 0.000000 0.0000000
## KMO 0.0000000 0.000000 0.0000000
## EXO1 0.0000000 0.000000 0.0000000
## AKT3 0.6931472 1.386294 0.6931472
## AAATTAATAAGCGCGA-1 AAATTACACGACTCTG-1 AAATTACCTATCGATG-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 1.098612 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.0000000 1.386294 1.386294
## AAATTCCAGGTCCAAA-1 AAATTGATAGTCCTTT-1 AAATTGGTGAGAAGCA-1
## CHRM3 0 0.000000 0.0000000
## FMN2 0 0.000000 0.0000000
## FH 0 0.000000 0.6931472
## KMO 0 0.000000 0.0000000
## EXO1 0 0.000000 0.0000000
## AKT3 0 1.098612 1.3862944
## AAATTTACCGAAATCC-1 AAATTTGCGGGTGTGG-1 AACAACTGGTAGTTGC-1
## CHRM3 0.0000000 0.0000000 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.6931472 0.0000000 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 1.0986123 0.6931472 1.386294
## AACAATACATTGTCGA-1 AACAATTACTCTACGC-1 AACACACGCTCGCCGC-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.0000000 1.386294 1.098612
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.098612 0.000000
## AACACGACTGTACTGA-1 AACACGAGACGCGGCC-1 AACAGCTGTGTGGCAA-1
## CHRM3 0.000000 0.000000 0.000000
## FMN2 0.000000 0.000000 0.000000
## FH 0.000000 0.000000 1.098612
## KMO 0.000000 0.000000 0.000000
## EXO1 0.000000 0.000000 0.000000
## AKT3 1.386294 1.098612 1.098612
## AACAGGAAATCGAATA-1 AACAGGATGGGCCGCG-1 AACAGGTAGTATGGAT-1
## CHRM3 0.000000 0.6931472 0.0000000
## FMN2 0.000000 0.0000000 0.0000000
## FH 1.098612 1.0986123 0.6931472
## KMO 0.000000 0.0000000 0.0000000
## EXO1 0.000000 0.0000000 0.0000000
## AKT3 0.000000 1.7917595 1.0986123
## AACATATCAACTGGTG-1 AACATCGATACGTCTA-1 AACATTGAAGTTGATC-1
## CHRM3 0.0000000 0.6931472 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.0000000 0.0000000 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 0.6931472 1.3862944 1.098612
## AACATTGTGACTCGAG-1 AACCAAGACTTCTCTG-1 AACCAGTATCACTCTT-1
## CHRM3 0.000000 0.0000000 0.000000
## FMN2 0.000000 0.0000000 0.000000
## FH 0.000000 0.0000000 0.000000
## KMO 0.000000 0.0000000 0.000000
## EXO1 0.000000 0.0000000 0.000000
## AKT3 1.386294 0.6931472 1.386294
## AACCATAGGGTTGAAC-1 AACCATGGGATCGCTA-1 AACCCAGAGACGGAGA-1
## CHRM3 0.000000 0.0000000 0.000000
## FMN2 0.000000 0.0000000 0.000000
## FH 1.098612 0.6931472 1.609438
## KMO 0.000000 0.0000000 0.000000
## EXO1 0.000000 0.0000000 0.000000
## AKT3 1.386294 1.0986123 1.386294
## AACCCATCCCATGATC-1 AACCCGACAACCCGTG-1 AACCCGAGCAGAATCG-1
## CHRM3 0.6931472 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.0000000 1.386294 1.386294
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.098612 0.000000
## AACCCGATAGGGCTTC-1 AACCCTACTGTCAATA-1 AACCCTGGTGGAACCA-1
## CHRM3 0.0000000 0.000000 0.0000000
## FMN2 0.0000000 0.000000 0.0000000
## FH 0.0000000 1.098612 0.0000000
## KMO 0.0000000 0.000000 0.0000000
## EXO1 0.0000000 0.000000 0.0000000
## AKT3 0.6931472 1.609438 0.6931472
## AACCGAGCTTGGTCAT-1 AACCGCTAAGGGATGC-1 AACCGTTGTGTTTGCT-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 1.098612 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.098612 1.098612
## AACCTAAAGCCGTCCG-1 AACCTCGCTTTAGCCC-1 AACCTGTCACGGAATT-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 0.000000 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.791759 1.098612
## AACCTTTAAATACGGT-1
## CHRM3 0.000000
## FMN2 0.000000
## FH 1.098612
## KMO 0.000000
## EXO1 0.000000
## AKT3 1.098612expr_g$gene=rownames(expr_g)
head(expr_g)## AAACAAGTATCTCCCA-1 AAACACCAATAACTGC-1 AAACAGAGCGACTCCT-1
## CHRM3 0.000000 0.0000000 0.000000
## FMN2 0.000000 0.0000000 0.000000
## FH 0.000000 0.6931472 0.000000
## KMO 0.000000 0.0000000 0.000000
## EXO1 0.000000 0.0000000 0.000000
## AKT3 1.609438 0.6931472 1.098612
## AAACAGCTTTCAGAAG-1 AAACAGGGTCTATATT-1 AAACATTTCCCGGATT-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 0.000000 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.609438 1.098612
## AAACCACTACACAGAT-1 AAACCCGAACGAAATC-1 AAACCGGAAATGTTAA-1
## CHRM3 0.000000 0 0.0000000
## FMN2 0.000000 0 0.0000000
## FH 0.000000 0 1.0986123
## KMO 0.000000 0 0.0000000
## EXO1 0.000000 0 0.0000000
## AKT3 1.791759 0 0.6931472
## AAACCGGGTAGGTACC-1 AAACCGTTCGTCCAGG-1 AAACCTAAGCAGCCGG-1
## CHRM3 0.0000000 0.000000 0.0000000
## FMN2 0.0000000 0.000000 0.0000000
## FH 0.6931472 0.000000 0.0000000
## KMO 0.0000000 0.000000 0.0000000
## EXO1 0.0000000 0.000000 0.0000000
## AKT3 2.0794415 1.386294 0.6931472
## AAACCTCATGAAGTTG-1 AAACGAAGAACATACC-1 AAACGACAGTCTTGCC-1
## CHRM3 0.000000 0.0000000 0.0000000
## FMN2 0.000000 0.0000000 0.0000000
## FH 1.098612 0.6931472 0.0000000
## KMO 0.000000 0.0000000 0.0000000
## EXO1 0.000000 0.0000000 0.0000000
## AKT3 1.098612 1.0986123 0.6931472
## AAACGAGACGGTTGAT-1 AAACGCCCGAGATCGG-1 AAACGCTGGGCACGAC-1
## CHRM3 0.0000000 0.0000000 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.0000000 0.6931472 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 0.6931472 1.0986123 1.386294
## AAACGGGCGTACGGGT-1 AAACGGTTGCGAACTG-1 AAACGTGTTCGCCCTA-1
## CHRM3 0.000000 0.000000 0.0000000
## FMN2 0.000000 0.000000 0.0000000
## FH 0.000000 0.000000 0.6931472
## KMO 0.000000 0.000000 0.0000000
## EXO1 0.000000 0.000000 0.0000000
## AKT3 1.386294 1.386294 1.0986123
## AAACTAACGTGGCGAC-1 AAACTCGGTTCGCAAT-1 AAACTCGTGATATAAG-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.0000000 0.0000000 0.0000000
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 0.6931472 0.6931472 0.6931472
## AAACTGCTGGCTCCAA-1 AAACTTAATTGCACGC-1 AAACTTGCAAACGTAT-1
## CHRM3 0 0.000000 0.000000
## FMN2 0 0.000000 0.000000
## FH 0 0.000000 1.098612
## KMO 0 0.000000 0.000000
## EXO1 0 0.000000 0.000000
## AKT3 0 1.386294 0.000000
## AAAGAATGTGGACTAA-1 AAAGACATGAAGTTTA-1 AAAGACCCAAGTCGCG-1
## CHRM3 0.000000 0.000000 0.000000
## FMN2 0.000000 0.000000 0.000000
## FH 0.000000 0.000000 0.000000
## KMO 0.000000 0.000000 0.000000
## EXO1 0.000000 0.000000 0.000000
## AKT3 1.386294 1.386294 1.386294
## AAAGACTGGGCGCTTT-1 AAAGCTTGCCTACATA-1 AAAGGCCCTATAATAC-1
## CHRM3 0.000000 0.000000 0.0000000
## FMN2 0.000000 0.000000 0.0000000
## FH 0.000000 0.000000 0.0000000
## KMO 0.000000 0.000000 0.0000000
## EXO1 0.000000 0.000000 0.0000000
## AKT3 1.386294 1.386294 0.6931472
## AAAGGCTACGGACCAT-1 AAAGGCTCTCGCGCCG-1 AAAGGGATGTAGCAAG-1
## CHRM3 0.000000 0.000000 0.0000000
## FMN2 0.000000 0.000000 0.0000000
## FH 0.000000 1.098612 0.6931472
## KMO 0.000000 0.000000 0.0000000
## EXO1 0.000000 0.000000 0.0000000
## AKT3 1.098612 1.098612 1.3862944
## AAAGGGCAGCTTGAAT-1 AAAGGTAAGCTGTACC-1 AAAGGTCAACGACATG-1
## CHRM3 0.0000000 0.0000000 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.6931472 1.0986123 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 1.3862944 0.6931472 1.098612
## AAAGTAGCATTGCTCA-1 AAAGTCACTGATGTAA-1 AAAGTCGACCCTCAGT-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.6931472 0.6931472 0.6931472
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 0.6931472 1.0986123 0.6931472
## AAAGTGCCATCAATTA-1 AAAGTGTGATTTATCT-1 AAAGTTGACTCCCGTA-1
## CHRM3 0.000000 0 0.0000000
## FMN2 0.000000 0 0.0000000
## FH 0.000000 0 0.6931472
## KMO 0.000000 0 0.0000000
## EXO1 0.000000 0 0.0000000
## AKT3 1.386294 0 1.9459101
## AAATAACCATACGGGA-1 AAATAAGGTAGTGCCC-1 AAATACCTATAAGCAT-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.6931472 0.6931472 0.0000000
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 1.3862944 1.3862944 0.6931472
## AAATAGCTTAGACTTT-1 AAATCACTCCTAAACG-1 AAATCCGATACACGCC-1
## CHRM3 0.0000000 0.0000000 0.0000000
## FMN2 0.0000000 0.0000000 0.0000000
## FH 0.6931472 0.6931472 0.0000000
## KMO 0.0000000 0.0000000 0.0000000
## EXO1 0.0000000 0.0000000 0.0000000
## AKT3 1.6094379 1.3862944 0.6931472
## AAATCTAGCCCTGCTA-1 AAATCTGCCCGCGTCC-1 AAATGATTCGATCAGC-1
## CHRM3 0 0.0000000 0.000000
## FMN2 0 0.0000000 0.000000
## FH 0 0.0000000 1.386294
## KMO 0 0.0000000 0.000000
## EXO1 0 0.0000000 0.000000
## AKT3 0 0.6931472 1.098612
## AAATGCTCGTTACGTT-1 AAATGGCATGTCTTGT-1 AAATGGCCCGTGCCCT-1
## CHRM3 0.000000 0 0.0000000
## FMN2 0.000000 0 0.0000000
## FH 0.000000 0 0.0000000
## KMO 0.000000 0 0.0000000
## EXO1 0.000000 0 0.0000000
## AKT3 1.098612 0 0.6931472
## AAATGGTCAATGTGCC-1 AAATGTATCTTATCCC-1 AAATTAACGGGTAGCT-1
## CHRM3 0.0000000 0.000000 0.0000000
## FMN2 0.0000000 0.000000 0.0000000
## FH 0.6931472 0.000000 0.0000000
## KMO 0.0000000 0.000000 0.0000000
## EXO1 0.0000000 0.000000 0.0000000
## AKT3 0.6931472 1.386294 0.6931472
## AAATTAATAAGCGCGA-1 AAATTACACGACTCTG-1 AAATTACCTATCGATG-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 1.098612 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.0000000 1.386294 1.386294
## AAATTCCAGGTCCAAA-1 AAATTGATAGTCCTTT-1 AAATTGGTGAGAAGCA-1
## CHRM3 0 0.000000 0.0000000
## FMN2 0 0.000000 0.0000000
## FH 0 0.000000 0.6931472
## KMO 0 0.000000 0.0000000
## EXO1 0 0.000000 0.0000000
## AKT3 0 1.098612 1.3862944
## AAATTTACCGAAATCC-1 AAATTTGCGGGTGTGG-1 AACAACTGGTAGTTGC-1
## CHRM3 0.0000000 0.0000000 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.6931472 0.0000000 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 1.0986123 0.6931472 1.386294
## AACAATACATTGTCGA-1 AACAATTACTCTACGC-1 AACACACGCTCGCCGC-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.0000000 1.386294 1.098612
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.098612 0.000000
## AACACGACTGTACTGA-1 AACACGAGACGCGGCC-1 AACAGCTGTGTGGCAA-1
## CHRM3 0.000000 0.000000 0.000000
## FMN2 0.000000 0.000000 0.000000
## FH 0.000000 0.000000 1.098612
## KMO 0.000000 0.000000 0.000000
## EXO1 0.000000 0.000000 0.000000
## AKT3 1.386294 1.098612 1.098612
## AACAGGAAATCGAATA-1 AACAGGATGGGCCGCG-1 AACAGGTAGTATGGAT-1
## CHRM3 0.000000 0.6931472 0.0000000
## FMN2 0.000000 0.0000000 0.0000000
## FH 1.098612 1.0986123 0.6931472
## KMO 0.000000 0.0000000 0.0000000
## EXO1 0.000000 0.0000000 0.0000000
## AKT3 0.000000 1.7917595 1.0986123
## AACATATCAACTGGTG-1 AACATCGATACGTCTA-1 AACATTGAAGTTGATC-1
## CHRM3 0.0000000 0.6931472 0.000000
## FMN2 0.0000000 0.0000000 0.000000
## FH 0.0000000 0.0000000 0.000000
## KMO 0.0000000 0.0000000 0.000000
## EXO1 0.0000000 0.0000000 0.000000
## AKT3 0.6931472 1.3862944 1.098612
## AACATTGTGACTCGAG-1 AACCAAGACTTCTCTG-1 AACCAGTATCACTCTT-1
## CHRM3 0.000000 0.0000000 0.000000
## FMN2 0.000000 0.0000000 0.000000
## FH 0.000000 0.0000000 0.000000
## KMO 0.000000 0.0000000 0.000000
## EXO1 0.000000 0.0000000 0.000000
## AKT3 1.386294 0.6931472 1.386294
## AACCATAGGGTTGAAC-1 AACCATGGGATCGCTA-1 AACCCAGAGACGGAGA-1
## CHRM3 0.000000 0.0000000 0.000000
## FMN2 0.000000 0.0000000 0.000000
## FH 1.098612 0.6931472 1.609438
## KMO 0.000000 0.0000000 0.000000
## EXO1 0.000000 0.0000000 0.000000
## AKT3 1.386294 1.0986123 1.386294
## AACCCATCCCATGATC-1 AACCCGACAACCCGTG-1 AACCCGAGCAGAATCG-1
## CHRM3 0.6931472 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.0000000 1.386294 1.386294
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.098612 0.000000
## AACCCGATAGGGCTTC-1 AACCCTACTGTCAATA-1 AACCCTGGTGGAACCA-1
## CHRM3 0.0000000 0.000000 0.0000000
## FMN2 0.0000000 0.000000 0.0000000
## FH 0.0000000 1.098612 0.0000000
## KMO 0.0000000 0.000000 0.0000000
## EXO1 0.0000000 0.000000 0.0000000
## AKT3 0.6931472 1.609438 0.6931472
## AACCGAGCTTGGTCAT-1 AACCGCTAAGGGATGC-1 AACCGTTGTGTTTGCT-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 1.098612 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.098612 1.098612
## AACCTAAAGCCGTCCG-1 AACCTCGCTTTAGCCC-1 AACCTGTCACGGAATT-1
## CHRM3 0.0000000 0.000000 0.000000
## FMN2 0.0000000 0.000000 0.000000
## FH 0.6931472 0.000000 0.000000
## KMO 0.0000000 0.000000 0.000000
## EXO1 0.0000000 0.000000 0.000000
## AKT3 0.6931472 1.791759 1.098612
## AACCTTTAAATACGGT-1 gene
## CHRM3 0.000000 CHRM3
## FMN2 0.000000 FMN2
## FH 1.098612 FH
## KMO 0.000000 KMO
## EXO1 0.000000 EXO1
## AKT3 1.098612 AKT3library(reshape2)
expr_g=melt(expr_g)
head(expr_g)## gene variable value
## 1 CHRM3 AAACAAGTATCTCCCA-1 0.000000
## 2 FMN2 AAACAAGTATCTCCCA-1 0.000000
## 3 FH AAACAAGTATCTCCCA-1 0.000000
## 4 KMO AAACAAGTATCTCCCA-1 0.000000
## 5 EXO1 AAACAAGTATCTCCCA-1 0.000000
## 6 AKT3 AAACAAGTATCTCCCA-1 1.609438expr_g$cluster=clus$cluster[match(expr_g$variable, clus$spot)]
expr_g=subset(expr_g, cluster%in%c("0", "1", "3"))
library(ggplot2)
library(ggpubr)ggplot(expr_g, aes(x=cluster, y=value))+geom_boxplot(notch = T)+theme_bw()+facet_wrap(~gene, scales = "free_y")+stat_compare_means(comparisons = list(c("0", "1"), c("0", "3"), c("1", "3")))
- Compare markers for all available clusters using an upset plot.
library(UpSetR)
colnames(mark)## [1] "gene" "marker_cluster0" "marker_cluster1" "marker_cluster2"
## [5] "marker_cluster3" "marker_cluster4" "marker_cluster5" "marker_cluster6"
## [9] "marker_cluster7" "marker_cluster8" "N_mark" # Define some vectors
group0 <- mark$gene[which(mark$marker_cluster0)]
group1 <- mark$gene[which(mark$marker_cluster1)]
group2 <- mark$gene[which(mark$marker_cluster2)]
group3 <- mark$gene[which(mark$marker_cluster3)]
group4 <- mark$gene[which(mark$marker_cluster4)]
group5 <- mark$gene[which(mark$marker_cluster5)]
group6 <- mark$gene[which(mark$marker_cluster6)]
group7 <- mark$gene[which(mark$marker_cluster7)]
group8 <- mark$gene[which(mark$marker_cluster8)]
# Make a names list with vectors
group_list=list("Cluster 0"=group0,
"Cluster 1"=group1,
"Cluster 2"=group2,
"Cluster 3"=group3,
"Cluster 4"=group4,
"Cluster 5"=group5,
"Cluster 6"=group6,
"Cluster 7"=group7,
"Cluster 8"=group8)# Make the upset
upset(fromList(group_list),nsets =9, order.by = "freq" )