Supplementary Figure 7
Florian Wuennemann
Last updated: 2024-03-21
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Knit directory: mi_spatialomics/
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Introduction
library(tidyverse)── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.5
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 3.4.4 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.0
✔ purrr 1.0.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(data.table)
Attaching package: 'data.table'
The following objects are masked from 'package:lubridate':
hour, isoweek, mday, minute, month, quarter, second, wday, week,
yday, year
The following objects are masked from 'package:dplyr':
between, first, last
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transposelibrary(ggbeeswarm)
library(patchwork)
source("./code/functions.R")
Attaching package: 'cowplot'
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align_plots
The following object is masked from 'package:lubridate':
stamp
here() starts at /Users/florian_wuennemann/1_Projects/MI_project/mi_spatialomicsb) SeqIF relative abundance of CCR2+ cells
data_path <- "./data/seqIF_regions_annotations/"
cell_locations <-
list.files(path = paste(data_path,"cell_locations",sep=""),pattern = "*.csv") %>%
setNames(., .) %>%
map_df(~fread(paste(paste(data_path,"cell_locations",sep=""),.,sep="/"), select= c("CellID","ROI")),
.id = "sample") %>%
mutate("fov" = gsub("annotated_|.csv","",sample))
region_measurements_full <-
list.files(path = paste(data_path,"ROI_measurements",sep=""),pattern = "*.txt") %>%
setNames(., .) %>%
map_df(~fread(paste(paste(data_path,"ROI_measurements",sep=""),.,sep="/")),
.id = "sample") %>%
mutate("fov" = gsub(".txt","",sample))
colnames(region_measurements_full) <- gsub(" ","_",colnames(region_measurements_full))
colnames(region_measurements_full) <- gsub("\\^","",colnames(region_measurements_full))
colnames(region_measurements_full) <- gsub("\\µ","u",colnames(region_measurements_full))
## Sum all individual annotations per sample and region
region_measurements <- region_measurements_full %>%
mutate("Area_um2" = if_else(fov %in% c("24h_86","4h_97"),Area_um2 * 0.235^2,Area_um2)) %>% ## Images that were post-registered using palom need to be size corrected, as their final pixel resolution is different
group_by(fov,Name) %>%
summarise("total_area_um2" = sum(Area_um2)) %>%
ungroup()`summarise()` has grouped output by 'fov'. You can override using the `.groups`
argument.Pixie output
pixie_cell_out <- fread("../data/SeqIF/pixie_cell_masks_0.05/cell_table_size_normalized_cell_labels.csv")
pixie_cell_out <- pixie_cell_out %>%
separate(fov,into = c("time","sample"), remove = FALSE) %>%
subset(cell_meta_cluster != "background") %>%
mutate("CellID" = label)Merge data
annotated_cells <- left_join(pixie_cell_out,cell_locations, by = c("fov","CellID"))
annotated_cells <- annotated_cells %>%
subset(ROI != "Background")
## Set factor level for time
annotated_cells$time <- factor(annotated_cells$time,
levels = c("Control","4h","24h","48h"))## Let's plot the number of cells per cell-type per sample
cells_per_region <- annotated_cells %>%
subset(!ROI %in% c("Unclassified","Ignore")) %>%
subset(!ROI %in% c("PathAnnotationObject","papillary_muscle","Lumen","Background",
"Ignore","RV_ignore","myocardium_control","remote_endocardium")) %>%
group_by(ROI,fov,time,cell_meta_cluster) %>%
tally()
cells_per_region_sub <- cells_per_region %>%
subset(grepl("Macro|Mono|Leuko|Neutro",cell_meta_cluster))
## Normalize cell numbers for area
region_measurements$ROI <- region_measurements$Name
cells_per_region_norm <- left_join(cells_per_region_sub,region_measurements, by = c("fov","ROI"))
cells_per_region_norm <- cells_per_region_norm %>%
mutate("cells_per_mm2" = n / total_area_um2 * 1000000) ## Normalize to square mmccr2_monomacro <- cells_per_region_norm %>%
subset(cell_meta_cluster == "Mono / Macros Ccr2+") %>%
subset(time %in% c("4h","24h","48h"))
ccr2_monomacro$ROI <- gsub("border_zone","Border zone",ccr2_monomacro$ROI)
ccr2_monomacro$ROI <- gsub("infarct_core","Infarct core",ccr2_monomacro$ROI)
ccr2_monomacro$ROI <- gsub("Epicardium","Epicardium",ccr2_monomacro$ROI)
ccr2_monomacro$ROI <- gsub("Endocardium","Endocardium",ccr2_monomacro$ROI)
ccr2_monomacro$ROI <- factor(ccr2_monomacro$ROI,
levels = c("Endocardium","Infarct core","Epicardium","Border zone"))
seqIF_ccr2_relquant <- ggplot(ccr2_monomacro,aes(x = time,y = cells_per_mm2)) +
stat_summary(
fun.y = mean,
geom = "bar",
width = 0.9,
size = 0.3,
color = "black",
fill = "lightgrey") +
geom_beeswarm(size = 2, pch = 21, color = "black", aes(fill = ROI)) +
labs(x = "Time",
y = expression("Cells /"~mm^2)) +
#expression(paste("Mo / M",phi," per "~mm^2))
facet_grid(. ~ ROI) +
scale_fill_manual(values = c("#337272","#f0f0f0","#b062c2","#2c95c5")) +
theme(axis.title = element_text(face="bold"),
legend.position = "none") +
theme(panel.border = element_rect(color = "black", fill = NA, size = 0.75)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1),
axis.title.x = element_blank()) Warning: The `fun.y` argument of `stat_summary()` is deprecated as of ggplot2 3.3.0.
ℹ Please use the `fun` argument instead.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
generated.Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
generated.Warning: The `size` argument of `element_rect()` is deprecated as of ggplot2 3.4.0.
ℹ Please use the `linewidth` argument instead.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
generated.seqIF_ccr2_relquant
c) Immunofluorescence relative abundance of CCR2+ cells
if_rel_counts <- fread("./data/Traditional_IF_relative_cell_counts.csv")
colnames(if_rel_counts) <- gsub(" ","_",colnames(if_rel_counts))
if_rel_counts <- if_rel_counts %>%
pivot_longer(cols = Endo_Pre:BZ_2d,
names_to = "sample",
values_to = "cell_count") %>%
separate(sample, into = c("region","timepoint"), sep = "_")
# Replace abbreviations with full labels
if_rel_counts$region <- gsub("Endo","Endocard",if_rel_counts$region)
if_rel_counts$region <- gsub("Core","Infarct core",if_rel_counts$region)
if_rel_counts$region <- gsub("Epi","Epicard",if_rel_counts$region)
if_rel_counts$region <- gsub("BZ","Border zone",if_rel_counts$region)
if_rel_counts$region <- factor(if_rel_counts$region, levels = c("Endocard","Infarct core","Epicard","Border zone"))
if_rel_counts$timepoint <- gsub("Pre","Control",if_rel_counts$timepoint)
if_rel_counts$timepoint <- gsub("1d","24h",if_rel_counts$timepoint)
if_rel_counts$timepoint <- gsub("2d","2 days",if_rel_counts$timepoint)
if_rel_counts$timepoint <- factor(if_rel_counts$timepoint, levels = c("Control","4h","24h","2 days"))
if_rel_counts <- subset(if_rel_counts,timepoint != "Control")
if_ccr2_relquant <- ggplot(if_rel_counts,aes(timepoint,cell_count)) +
stat_summary(
fun.y = mean,
geom = "bar",
width = 0.9,
size = 0.3,
color = "black",
fill = "lightgrey") +
labs(x = "Time",
y = expression("Cells /"~mm^2)) +
geom_beeswarm(size = 2 , pch = 21, color = "black", aes(fill = region)) +
facet_grid(.~ region) +
theme(axis.title = element_text(face="bold"),
legend.position = "none") +
scale_fill_manual(values = c("#337272","#f0f0f0","#b062c2","#2c95c5")) +
theme(panel.border = element_rect(color = "black", fill = NA, size = 0.75)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1),
axis.title.x = element_blank())
## Combine plots
joined_plot <- seqIF_ccr2_relquant | if_ccr2_relquant
save_plot(filename = "./plots/supp_figure_7.tradIF-relative_cell_counts.pdf",
plot = joined_plot,
base_asp = 3,
base_height = 4)
sessionInfo()R version 4.3.1 (2023-06-16)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.1.2
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Berlin
tzcode source: internal
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] RColorBrewer_1.1-3 here_1.0.1 ggsci_3.0.0 cowplot_1.1.2
[5] patchwork_1.2.0 ggbeeswarm_0.7.2 data.table_1.14.10 lubridate_1.9.3
[9] forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2
[13] readr_2.1.5 tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.4
[17] tidyverse_2.0.0 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] gtable_0.3.4 beeswarm_0.4.0 xfun_0.41
[4] bslib_0.6.1 processx_3.8.3 callr_3.7.3
[7] tzdb_0.4.0 vctrs_0.6.5 tools_4.3.1
[10] ps_1.7.6 generics_0.1.3 fansi_1.0.6
[13] highr_0.10 pkgconfig_2.0.3 lifecycle_1.0.4
[16] farver_2.1.1 compiler_4.3.1 git2r_0.33.0
[19] textshaping_0.3.7 munsell_0.5.0 getPass_0.2-4
[22] vipor_0.4.7 httpuv_1.6.14 htmltools_0.5.7
[25] sass_0.4.8 yaml_2.3.8 crayon_1.5.2
[28] later_1.3.2 pillar_1.9.0 jquerylib_0.1.4
[31] whisker_0.4.1 cachem_1.0.8 tidyselect_1.2.0
[34] digest_0.6.34 stringi_1.8.3 labeling_0.4.3
[37] rprojroot_2.0.4 fastmap_1.1.1 grid_4.3.1
[40] colorspace_2.1-0 cli_3.6.2 magrittr_2.0.3
[43] utf8_1.2.4 withr_2.5.2 scales_1.3.0
[46] promises_1.2.1 timechange_0.2.0 rmarkdown_2.25
[49] httr_1.4.7 ragg_1.2.7 hms_1.1.3
[52] evaluate_0.23 knitr_1.45 rlang_1.1.3
[55] Rcpp_1.0.12 glue_1.7.0 BiocManager_1.30.22
[58] renv_1.0.3 rstudioapi_0.15.0 jsonlite_1.8.8
[61] R6_2.5.1 systemfonts_1.0.5 fs_1.6.3