Supplementary Figure 2
Nils Eling and Nicolas Damond
2020-11-18
Last updated: 2020-11-18
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Knit directory: cytomapper_publication/
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This script reproduces the analysis performed in Supplementary Figure 2. Here, we will load the libraries and data for this figure:
library(cytomapper)
library(dplyr)
sce <- readRDS("data/PancreasData/pancreas_sce.rds")
images <- readRDS("data/PancreasData/pancreas_images.rds")In line with Supplementary Figure 1, we will now order the images based on the mean intensity of all PIN positive pixels.
PIN_mean <- unlist(lapply(images,
function(x){
cur_x <- x[,,"PIN"]
mean(cur_x[cur_x > 0])
}))Here, we will visualize the marker pro-insulin (PIN) across all images. Due to the progressive decline in beta cell function, we expect PIN expression to be reduced in Long-Duration patients. However, a similar analysis can be performed to visually detect image-to-image irregularities in background stain.
We will normalize across all images to keep the differences in staining intensity between images intact.
# Specify the image order
cur_order <- order(PIN_mean, decreasing = TRUE)
# Collect metadata for images
cur_meta <- as_tibble(colData(sce)) %>%
group_by(ImageNumber) %>%
summarise_at(vars("ImageName", "ImageFullName", "stage"), unique) %>%
mutate(ImageFullName = gsub(".tiff", "", ImageFullName)) %>%
as.data.frame()
rownames(cur_meta) <- cur_meta$ImageFullName
cur_meta <- cur_meta[names(PIN_mean)[cur_order],]
images <- normalize(images)
images <- normalize(images, inputRange = c(0, 0.05))
plotPixels(image = images[cur_order],
colour_by = "PIN",
scale_bar = list(length = 100,
label = "",
colour = "white"),
colour = list(PIN = c("black", "yellow")),
legend = list(margin = 100),
image_title = list(text = cur_meta$stage,
colour = "white"))
# Save plot
plotPixels(image = images[cur_order],
colour_by = "PIN",
scale_bar = list(length = 100,
label = "",
colour = "white"),
colour = list(PIN = c("black", "yellow")),
legend = list(margin = 100,
colour_by.title.cex = 8,
colour_by.labels.cex = 4),
image_title = list(text = cur_meta$stage,
colour = "white",
cex = 3),
save_plot = list(filename = "docs/final_figures/supplements/Fig_S2.png"))Here, we see the progressive decline in beta cell fractions. The images are ordered based on T1D stage: Non-diabetic, Onset and Long-Duration, as expected. We further see an increased morphological irregularity in Long-Duration islets.
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.1 LTS
Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=C
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] dplyr_1.0.2 cytomapper_1.2.0
[3] SingleCellExperiment_1.12.0 SummarizedExperiment_1.20.0
[5] Biobase_2.50.0 GenomicRanges_1.42.0
[7] GenomeInfoDb_1.26.0 IRanges_2.24.0
[9] S4Vectors_0.28.0 BiocGenerics_0.36.0
[11] MatrixGenerics_1.2.0 matrixStats_0.57.0
[13] EBImage_4.32.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] viridis_0.5.1 viridisLite_0.3.0 svgPanZoom_0.3.4
[4] shiny_1.5.0 sp_1.4-4 GenomeInfoDbData_1.2.4
[7] vipor_0.4.5 tiff_0.1-6 yaml_2.2.1
[10] gdtools_0.2.2 pillar_1.4.6 lattice_0.20-41
[13] glue_1.4.2 digest_0.6.27 RColorBrewer_1.1-2
[16] promises_1.1.1 XVector_0.30.0 colorspace_2.0-0
[19] htmltools_0.5.0 httpuv_1.5.4 Matrix_1.2-18
[22] pkgconfig_2.0.3 raster_3.4-5 zlibbioc_1.36.0
[25] purrr_0.3.4 xtable_1.8-4 fftwtools_0.9-9
[28] scales_1.1.1 svglite_1.2.3.2 whisker_0.4
[31] jpeg_0.1-8.1 later_1.1.0.1 git2r_0.27.1
[34] tibble_3.0.4 generics_0.1.0 ggplot2_3.3.2
[37] ellipsis_0.3.1 magrittr_2.0.1 crayon_1.3.4
[40] mime_0.9 evaluate_0.14 fs_1.5.0
[43] beeswarm_0.2.3 shinydashboard_0.7.1 tools_4.0.3
[46] lifecycle_0.2.0 stringr_1.4.0 munsell_0.5.0
[49] locfit_1.5-9.4 DelayedArray_0.16.0 compiler_4.0.3
[52] systemfonts_0.3.2 rlang_0.4.8 grid_4.0.3
[55] RCurl_1.98-1.2 rstudioapi_0.13 htmlwidgets_1.5.2
[58] bitops_1.0-6 rmarkdown_2.5 gtable_0.3.0
[61] codetools_0.2-18 abind_1.4-5 R6_2.5.0
[64] gridExtra_2.3 knitr_1.30 fastmap_1.0.1
[67] rprojroot_2.0.2 stringi_1.5.3 ggbeeswarm_0.6.0
[70] Rcpp_1.0.5 vctrs_0.3.5 png_0.1-7
[73] tidyselect_1.1.0 xfun_0.19