Last updated: 2026-09-10

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Knit directory: immgenT-GP-analysis/analysis/

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Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/FigureS4.Rmd) and HTML (docs/FigureS4.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
Rmd dca7ffb Ziang Zhang 2026-09-10 Strip the code-narrating prose from every page; fold code chunks by default
html 54718c4 Ziang Zhang 2026-09-10 Build site: the four mean-loading heatmaps without their titles
html 936ed6e Ziang Zhang 2026-09-10 Build site: Extended Data 2d without the DP lineage
html 59021bf Ziang Zhang 2026-09-10 Build site: Extended Data 1-6 after removing the structure-plot figure
Rmd c21f51f Ziang Zhang 2026-09-10 Remove the per-lineage structure-plot figure; keep its record for Figure 4
html c21f51f Ziang Zhang 2026-09-10 Remove the per-lineage structure-plot figure; keep its record for Figure 4
html 60125af Ziang Zhang 2026-09-10 Build site: Figure 4b on the shared column colours
html 88ee847 Ziang Zhang 2026-09-10 Build site: Figure 4b without the miniverse clusters
html 5874416 Ziang Zhang 2026-09-10 Build site: main Figure 4 inserted, Extended Data back to 1-7
Rmd 4307b28 Ziang Zhang 2026-09-10 New main Figure 4, and fold the cluster heatmap into Extended Data Figure 2
html a7a481f Ziang Zhang 2026-09-09 Build site: the rebuilt Figure 1d and the Extended Data renumbering
Rmd c233cd8 Ziang Zhang 2026-09-09 Extended Data reorganisation: split the tissue/cluster figure, renumber 3-8
html 1e88d7e Ziang Zhang 2026-09-04 Build site: published captions and titles across all 24 pages
Rmd 0267e5b Ziang Zhang 2026-09-04 Captions from the published manuscript; trim editor notes off the page code
html 19c977f Ziang Zhang 2026-09-02 Build site: Extended Data 5-7 renumbered, Figure S5 page rebuilt
html cbcec52 Ziang Zhang 2026-07-30 Build site: Extended Data Figure naming
Rmd 66aa029 Ziang Zhang 2026-07-30 Name the Extended Data figures as published on the site
html ac650a0 Ziang Zhang 2026-07-30 Build site: Figure S5 (ex-S6a) and Figure S6 as a-f
html ae21d37 Ziang Zhang 2026-07-28 Build site: republish after the reorder commits
html d538aa2 Ziang Zhang 2026-07-28 Build site: reordered Figures 6 / S6 / S3 and the new Figure 7b page
html 029b0ae Ziang Zhang 2026-07-28 Build site.
Rmd 0f5b5da Ziang Zhang 2026-07-28 Align all figure captions with captions_20260728_final.docx
html 3fc3789 Ziang Zhang 2026-07-27 Republish all 24 pages
html 1390a03 Ziang Zhang 2026-07-27 Republish all 24 pages
html adaef21 Ziang Zhang 2026-07-27 Build site: panel fixes and PDF-derived assets
html 5b19858 Ziang Zhang 2026-07-27 Build site.
Rmd 91ee059 Ziang Zhang 2026-07-26 Select each panel’s code block by name, not by line number
html 91ee059 Ziang Zhang 2026-07-26 Select each panel’s code block by name, not by line number
Rmd 3c052d6 Ziang Zhang 2026-07-15 Finalize full-centered Figure S4
html 3c052d6 Ziang Zhang 2026-07-15 Finalize full-centered Figure S4
Rmd 8938a27 Ziang Zhang 2026-07-14 Update Figure S4 centered heatmaps
html 8938a27 Ziang Zhang 2026-07-14 Update Figure S4 centered heatmaps
Rmd c344aaa Ziang Zhang 2026-07-13 Add Figure S4 mean-loading heatmaps
html c344aaa Ziang Zhang 2026-07-13 Add Figure S4 mean-loading heatmaps

Produced by script/FigureS4.R. The code below is shown for reference; the image is its pre-rendered output.

Setup

library(dplyr)
library(pheatmap)
library(Matrix) # protein matrices are dgCMatrix; must be attached for `[` to dispatch

data_path <- "data/"
figure_path <- "figures/final-selected/Figure S4/"
source("code/R/citeseq_shared_setup.R")

# Record when this run started, to assert at the end that the panel is newer.
run_started_at <- Sys.time()

Protein-program heatmap

# ============================================================
# s4: sparse protein-program heatmap, contamination GPs removed
# ============================================================
# The normalized protein matrix is derived here rather than in
# citeseq_shared_setup.R because this is its only consumer among the figures.
Protein_F_pm <- Protein_F_pm_raw[!rownames(Protein_F_pm_raw) %in% isotype_proteins, ]
Protein_F_pm <- Protein_F_pm[rownames(Protein_F_pm) %in% good_proteins, ]
Protein_F_pm <- Protein_F_pm[!rownames(Protein_F_pm) %in% exclude_proteins, ]
Protein_F_pm <- Protein_F_pm[!rownames(Protein_F_pm) %in% thy11_proteins, ]
D_lognorm <- diag(1 / apply(Protein_F_pm, 2, function(x) max(abs(x))))
Protein_F_pm <- Protein_F_pm %*% D_lognorm
colnames(Protein_F_pm) <- paste0("GP", 1:ncol(Protein_F_pm))
Protein_F_pm[is.na(Protein_F_pm)] <- 0

threshold_simplified <- 0
keep_rows_simplified <- apply(Protein_F_pm, 1, function(v) any(abs(v) > threshold_simplified, na.rm = TRUE))
Protein_F_pm_simplified <- Protein_F_pm[keep_rows_simplified, , drop = FALSE]
keep_cols_simplified <- apply(Protein_F_pm_simplified, 2, function(v) any(abs(v) > threshold_simplified, na.rm = TRUE))
Protein_F_pm_simplified <- Protein_F_pm_simplified[, keep_cols_simplified, drop = FALSE]

GP_contamination <- c("GP40", "GP50", "GP55", "GP188")
Protein_F_pm_simplified_no_contamination <- Protein_F_pm_simplified[, !colnames(Protein_F_pm_simplified) %in% GP_contamination, drop = FALSE]

sparse_cutoff <- 0.5
bk_sparse <- unique(c(seq(-1, -sparse_cutoff, length.out = 26), seq(-sparse_cutoff, sparse_cutoff, length.out = 51), seq(sparse_cutoff, 1, length.out = 26)))
cols_sparse <- c(colorRampPalette(c("#4575B4", "white"))(25), rep("white", 50), colorRampPalette(c("white", "#D73027"))(25))

# Display proteins as rows and GPs as columns. Order GP columns from most to
# fewest visible proteins. Order protein rows by their rightmost visible GP, so
# proteins extending into the sparse right side appear first and form a
# triangular boundary. Visible count and a rarity-weighted support score provide
# deterministic secondary ordering.
wide_matrix_s4 <- as.matrix(Protein_F_pm_simplified_no_contamination)
wide_visible_mask_s4 <- abs(wide_matrix_s4) >= sparse_cutoff
wide_gp_visible_count_s4 <- colSums(wide_visible_mask_s4)
wide_protein_visible_count_s4 <- rowSums(wide_visible_mask_s4)
wide_gp_number_s4 <- as.integer(sub("^GP", "", colnames(wide_matrix_s4)))

wide_gp_order_s4 <- order(-wide_gp_visible_count_s4, wide_gp_number_s4)
wide_mask_ordered_cols_s4 <- wide_visible_mask_s4[
  ,
  wide_gp_order_s4,
  drop = FALSE
]
wide_rightmost_visible_gp_s4 <- apply(
  wide_mask_ordered_cols_s4,
  1,
  function(values) max(which(values))
)
wide_rarity_weights_s4 <- seq_len(ncol(wide_mask_ordered_cols_s4))^2
wide_protein_rarity_score_s4 <- as.numeric(
  wide_mask_ordered_cols_s4 %*% wide_rarity_weights_s4
)
wide_protein_order_s4 <- order(
  -wide_rightmost_visible_gp_s4,
  -wide_protein_visible_count_s4,
  -wide_protein_rarity_score_s4,
  rownames(wide_matrix_s4)
)
wide_ordered_matrix_s4 <- wide_matrix_s4[
  wide_protein_order_s4,
  wide_gp_order_s4,
  drop = FALSE
]

pdf(paste0(figure_path, "s4.pdf"), width = 48, height = 14)
pheatmap::pheatmap(
  wide_ordered_matrix_s4,
  main = sprintf(
    paste0(
      "Protein programs - GP columns, triangular-first protein rows ",
      "(|score| >= %.1f; protein-row sparsity is not monotone)"
    ),
    sparse_cutoff
  ),
  color = cols_sparse,
  breaks = bk_sparse,
  cluster_rows = FALSE,
  cluster_cols = FALSE,
  border_color = "grey75",
  fontsize = 16,
  fontsize_row = 16,
  fontsize_col = 16,
  angle_col = 90,
  legend_breaks = c(-1, -sparse_cutoff, 0, sparse_cutoff, 1),
  legend_labels = c("-1", "-0.5", "0 (white)", "0.5", "1")
)
dev.off()

Version Author Date
c21f51f Ziang Zhang 2026-09-10
5874416 Ziang Zhang 2026-09-10

Extended Data Fig. 4. Heatmap of scaled protein scores for each GP. We focused on the 47 proteins that performed best in the immgenT CITE-seq dataset.


sessionInfo()
R version 4.5.1 (2025-06-13)
Platform: aarch64-apple-darwin20
Running under: macOS Sequoia 15.6.1

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1

locale:
[1] en_CA/en_CA/en_CA/C/en_CA/en_CA

time zone: America/Chicago
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] vctrs_0.7.3     cli_3.6.6       knitr_1.50      rlang_1.2.0    
 [5] xfun_0.55       stringi_1.8.9   otel_0.2.0      promises_1.5.0 
 [9] jsonlite_2.0.0  workflowr_1.7.2 glue_1.8.1      rprojroot_2.1.1
[13] git2r_0.36.2    htmltools_0.5.9 httpuv_1.6.16   sass_0.4.10    
[17] rmarkdown_2.30  evaluate_1.0.5  jquerylib_0.1.4 tibble_3.3.0   
[21] fastmap_1.2.0   yaml_2.3.12     lifecycle_1.0.5 whisker_0.4.1  
[25] stringr_1.6.0   compiler_4.5.1  fs_1.6.6        Rcpp_1.1.1-1.1 
[29] pkgconfig_2.0.3 later_1.4.4     digest_0.6.39   R6_2.6.1       
[33] pillar_1.11.1   magrittr_2.0.5  bslib_0.9.0     tools_4.5.1    
[37] cachem_1.1.0