Risperidone regulates the expression of schizophrenia-related genes in the forebrain of adult male mice.

Code ↔ Paper

7 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 7 matches · 2 of them tie a paragraph to a whole file without given lines: weak matches, whose lines are not tinted

[1] § Results › Spatial patterns of gene expression in the forebrain ↔ preprocessing/functions/umap_feature_expression_plot.R, lines 195 to 263 · score 0.68 · Adora2a, Ppp1r2, Drd1, Drd2, Ecel1, Gad2 · Report a mismatch
[2] § Results › Spatial patterns of gene expression in the forebrain ↔ preprocessing/risperidone/ris-umap-genes.R, the whole file · a weak match · score 0.67 · Adora2a, Ppp1r2, Drd1, Drd2, Ecel1, Gad2 · Report a mismatch
[3] § Methods › Cluster identification and marker validation ↔ preprocessing/functions/functions-spatial-data.R, lines 71 to 132 · score 0.66 · Principal component, Seurat, UMAP, neighbor, variable · Report a mismatch
[4] § Methods › Cluster identification and marker validation ↔ preprocessing/old-scripts/deseq-test-analysis.R, lines 392 to 476 · score 0.64 · variance stabilizing transformation, log2 fold change, Clusters · Report a mismatch
[5] § Methods › Differential gene expression analysis ↔ preprocessing/functions/statistics-functions-v2.R, lines 186 to 234 · score 0.57 · log2 fold change, quantile normalization, assignments, clustering resolution, transcript · Report a mismatch
[6] § Methods › Peak processing, validation, and custom reference generation ↔ preprocessing/old-scripts/reduction-peaks.R, lines 333 to 414 · score 0.52 · amplitude, log10, coverage, BAM, summit, ratio · Report a mismatch
[7] § Results › Enrichment analysis ↔ preprocessing/clozapine/supplementaryAnalysis_paper_03.12.2025.R, the whole file · a weak match · score 0.50 · Cacna1i, Bhlhe40, Phactr3, Homer1, Kalrn, Olig2 · Report a mismatch

Paper

Loaded from Europe PMC by your browser; OSCR does not store it: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The paper is loaded by your browser, with JavaScript: read it at doi.org or on Europe PMC.

The authors' code

R · 267 lines · 10 KB · no license · 1 match

umap_feature_expression_plot <- function(ldopa_integrate,
spatial_data,
type_data,
peak_id,
samples,
plot_title = "UMAP Visualization with Feature Expression", # Nowy argument dla tytułu
min_percentile = 0.01,
max_percentile = 0.99,
normalization = TRUE,
low_color = "gray99",
high_color = "red",
na_color = "grey99",
point_size = 1,
alpha = 1,
save_to_png = FALSE, # Nowy argument: czy zapisać do PNG
file_path = NULL, # Nowy argument: ścieżka do zapisu
width = 8, # Opcjonalny argument: szerokość wykresu
height = 6, # Opcjonalny argument: wysokość wykresu
dpi = 300) { # Opcjonalny argument: rozdzielczość
# Wyciągnij koordynaty UMAP oraz barcodes
umap_coordinates <- ldopa_integrate@reductions$[email hidden]
umap_table <- data.frame(
barcode = rownames(umap_coordinates),
X = umap_coordinates[, 1], # Oś X
Y = umap_coordinates[, 2] # Oś Y
)
# Przygotowanie tabeli ekspresji
expression_table <- spatial_data[[type_data]]$data[peak_id, ] %>%
as.data.frame() %>%
dplyr::rename(expression = ".") %>%
rownames_to_column("sample_barcode") %>%
separate("sample_barcode", c("sample", "barcode"), sep = "_") %>%
left_join(., spatial_data$bcs_information, by = c("barcode", "sample")) %>%
filter(sample %in% samples) %>%
mutate(
max_perc = as.numeric(quantile(expression, probs = c(max_percentile), na.rm = TRUE)),
min_perc = as.numeric(quantile(expression, probs = c(min_percentile), na.rm = TRUE)),
expression = ifelse(expression > max_perc, max_perc, expression),
expression = ifelse(expression < min_perc, min_perc, expression),
expression = if (normalization == TRUE) {
(expression - min(expression, na.rm = TRUE)) / (max(expression, na.rm = TRUE) - min(expression, na.rm = TRUE))
} else {
expression
},
barcode = paste(sample, barcode, sep = "_")
) %>%
dplyr::select(barcode, expression)
# Merge dwóch tabel
merged_table <- dplyr::left_join(umap_table, expression_table, by = "barcode")
# Sprawdzenie poprawności mergu
all_matched <- nrow(merged_table) == nrow(umap_table)
missing_matches <- sum(is.na(merged_table$expression))
if (!all_matched || missing_matches > 0) {
cat("Uwaga: Niektóre wiersze nie zostały dopasowane. Niedopasowane wiersze:", missing_matches, "\n")
}
# Tworzenie wykresu
plot <- ggplot(merged_table, aes(x = X, y = Y, fill = expression)) +
geom_point(shape = 21, size = point_size, alpha = alpha, stroke = 0) + # Punkty bez obramówki
scale_fill_gradient(low = low_color, high = high_color, na.value = na_color) + # Skala kolorów
labs(
title = plot_title, # Użycie nowego argumentu dla tytułu
x = "UMAP 1",
y = "UMAP 2",
fill = "Expression"
) +
theme_minimal() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "black")
)
# Opcjonalny zapis do pliku
if (save_to_png) {
# Ustawienie domyślnej ścieżki, jeśli nie została podana
if (is.null(file_path)) {
file_path <- getwd()
}
# Upewnienie się, że ścieżka istnieje
if (!dir.exists(file_path)) {
dir.create(file_path, recursive = TRUE)
cat("Utworzono katalog:", file_path, "\n")
}
# Przygotowanie bezpiecznej nazwy pliku
safe_title <- stringr::str_replace_all(plot_title, "[: ]", "_")
safe_title <- stringr::str_replace_all(safe_title, "_+", "_")
file_name <- paste0(safe_title, ".png")
full_path <- file.path(file_path, file_name)
# Dostosowanie motywu do białego tła
plot_to_save <- plot + theme(
panel.background = element_rect(fill = "white", color = NA),
plot.background = element_rect(fill = "white", color = NA)
)
# Zapis wykresu
ggsave(filename = full_path, plot = plot_to_save, width = width, height = height, dpi = dpi)
cat("Wykres zapisano do pliku:", full_path, "\n")
}
return(plot)
}
#
# # Wywołanie funkcji z Twoimi danymi
# plot <- umap_feature_expression_plot(
# ldopa_integrate = ldopa_integrate,
# spatial_data = ldopa_st_data,
# type_data = "quantile_normalize_resolution_1",
# peak_id = "ldopa-peak-17758",
# samples = c(samples_saline, samples_ldopa),
# min_percentile = 0.00,
# max_percentile = 1,
# normalization = TRUE,
# low_color = "gray99",
# high_color = "red",
# na_color = "grey99",
# point_size = 1,
# alpha = 1
# )
#
# # Wyświetlenie wykresu
# print(plot)
umap_gene_expression_plot <- function(spatial_data,
type_data,
ncol,
gene,
ldopa_integrate,
samples,
min_percentile = 0.01,
max_percentile = 0.99,
normalization = TRUE,
low_color = "gray95",
high_color = "red",
na_color = "grey99",
point_size = 1,
alpha = 1,
save_to_png = FALSE, # Nowy argument: czy zapisać do PNG
file_path = NULL, # Nowy argument: ścieżka do zapisu
width = 8, # Opcjonalny argument: szerokość wykresu
height = 6, # Opcjonalny argument: wysokość wykresu
dpi = 300, # Opcjonalny argument: rozdzielczość
...) {
# Wyciągnięcie wektora peak_id dla danego genu
vector_peak <- spatial_data[[type_data]]$annotate %>%
dplyr::filter(gene_name == gene) %>%
dplyr::select(peak_id) %>%
pull(peak_id)
print(paste("Peaki dla genu", gene, ":", paste(vector_peak, collapse = ", ")))
# Lista do przechowywania wykresów
plot_list <- list()
# Iteracja po każdym peak_id
for (peak in vector_peak) {
# Tworzenie tytułu wykresu
plot_title <- paste(gene, peak, sep = ": ")
# Generowanie wykresu UMAP
plot <- umap_feature_expression_plot(
ldopa_integrate = ldopa_integrate,
spatial_data = spatial_data,
type_data = type_data,
peak_id = peak,
samples = samples,
plot_title = plot_title,
min_percentile = min_percentile,
max_percentile = max_percentile,
normalization = normalization,
low_color = low_color,
high_color = high_color,
na_color = na_color,
point_size = point_size,
alpha = alpha,
save_to_png = save_to_png, # Przekazanie argumentu
file_path = file_path, # Przekazanie argumentu
width = width, # Przekazanie argumentu
height = height, # Przekazanie argumentu
dpi = dpi # Przekazanie argumentu
)
# Dodanie wykresu do listy
plot_list[[peak]] <- plot
# Opcjonalne wyświetlenie wykresu
print(plot_title)
print(plot)
}
# Organizacja wykresów w siatkę
combined_plot <- patchwork::wrap_plots(plot_list, ncol = ncol, guides = "collect") +
patchwork::plot_annotation(title = paste("UMAP Plots dla Genu:", gene))
# Wyświetlenie połączonego wykresu
print(combined_plot)
# Opcjonalny zapis połączonego wykresu
if (save_to_png) {
# Ustawienie domyślnej ścieżki, jeśli nie została podana
if (is.null(file_path)) {
file_path <- getwd()
}
# Upewnienie się, że ścieżka istnieje
if (!dir.exists(file_path)) {
dir.create(file_path, recursive = TRUE)
cat("Utworzono katalog:", file_path, "\n")
}
# Przygotowanie bezpiecznej nazwy pliku
safe_title <- gsub("[/:*?\"<>|\\s]", "_", paste("Combined_", gene, sep = ""))
file_name <- paste0(safe_title, ".png")
full_path <- file.path(file_path, file_name)
# # Zapis połączonego wykresu
# ggsave(filename = full_path, plot = combined_plot, width = width, height = height, dpi = dpi)
# cat("Połączony wykres zapisano do pliku:", full_path, "\n")
}
# Zwrócenie listy wykresów oraz połączonego wykresu
return(list(individual_plots = plot_list, combined_plot = combined_plot))
}
umap_gene_expression_plot(
spatial_data = risperidone_st_data_half,
type_data = "quantile_normalize_resolution_0.4",
ncol = 2,
gene = "Gad2",
ldopa_integrate = risperidone_integrate_half,
samples = c(samples_saline, samples_risperidone),
min_percentile = 0.01,
max_percentile = 0.99,
normalization = TRUE,
low_color = "gray95",
high_color = "red",
na_color = "grey99",
point_size = 1.5,
alpha = 1,
save_to_png = TRUE, # Włączenie zapisu do PNG
file_path = "./results/risperidone/umap-gene-expression", # Podanie ścieżki do katalogu
width = 10, # Szerokość wykresu w calach
height = 8, # Wysokość wykresu w calach
dpi = 300 # Rozdzielczość
)
# Definiowanie wektora z nazwami genów
genes <- c("Drd1", "Drd2", "Adora2a", "Ppp1r1b", "Ppp1r2", "Gad2", "Ecel1", "Gfra1")

umap_feature_expression_plot.R at commit 03f0a59, no license · at the source

Overview

Authors: Magdalena Ziemiańska¹, Mateusz Zięba², Anna Radlicka-Borysewska¹, Łukasz Szumiec¹, Sławomir Gołda¹, Małgorzata Borczyk², Marcin Piechota², Michał Korostyński², Jan Rodriguez Parkitna¹

Institutions: Maj Institute of Pharmacology (Poland); Polish Academy of Sciences (Poland)

Journal: Frontiers in molecular neuroscience, volume 19, article 1844705

Dates: received 1 April 2026; accepted 12 May 2026; published online 29 May 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.3389/fnmol.2026.1844705 · PMID 42293048 · PMCID PMC13260059 · OpenAlex W7162765275

Open access: gold, a free copy (OpenAlex)

Status: code verified (how the code is found and verified)

Categories: genetics / omics (modality), mouse (organism), schizophrenia / psychosis (population), cellular / molecular (subfield)

Methods: Statistics, Smoothing, state filtering, decompositions, Preprocessing

Keywords: antipsychotics, forebrain, gene expression, mouse, risperidone, schizophrenia, spatial transcriptomics

Topic: Neurogenesis and neuroplasticity mechanisms (Developmental Neuroscience, Neuroscience), according to OpenAlex

Citations: not cited yet (Europe PMC); 79 references in the paper

Research resources: RRID:SCR_001575, RRID:SCR_002105, RRID:SCR_014583, 000 Sequencing System RRID:SCR_016387, RRID:SCR_018555, 100 RRID:SCR_019715, RRID:SCR_020214, RRID:SCR_023571, RRID:SCR_025848

Abstract

Introduction: Risperidone is a widely used antipsychotic that reduces psychotic symptoms through modulation of monoaminergic signaling. At the cellular level, however, its effects extend beyond receptor antagonism and induce spatially discrete transcriptional responses across forebrain structures, particularly in the basal ganglia and frontal cortex.

Methods: We applied sequencing-based spatial transcriptomics to the forebrain of male C57BL/6N mice following acute risperidone treatment (0.5 mg/kg, i.p.). Unsupervised clustering of spatial transcriptomic profiles accurately delineated cortical divisions, cortical layers, and basal ganglia subregions. Differential expression analysis within anatomically defined clusters, performed using a customized statistical framework, revealed transcriptional patterns that were highly structure-specific and distinct between cortical and basal ganglia regions.

Results: Acute risperidone treatment significantly affected 95 transcripts across 12 brain regions. The most prominent transcriptional changes were concentrated in ventral forebrain structures, including the olfactory tubercle (25 differentially expressed transcripts), diagonal band nucleus (22), corpus callosum and commissures (13), and lateral septal nucleus (9). Importantly, 18 of these 95 genes have previously been implicated in schizophrenia, including Olig2, Smpd3, and Cacna1i.

Discussion: Together, these findings indicate that acute treatment with risperidone in male mice exerts pronounced molecular effects in medial and ventral forebrain regions with high oligodendrocyte and glial cell abundance. Moreover, enrichment analysis points to a molecular convergence between risperidone-induced transcription and genetic pathways implicated in schizophrenia.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 7 matches between paragraphs and lines of code.

macs3-project/MACS

License: BSD-3-Clause

State: the link answers, verified on 29 October 2026

Evidence: files inventoried

Commit: c6706103a402d1a2eb84fe9cde841dbc0cb35d9b, 28 October 2026

Languages: Python (148), C/C++ (35), C (23), Jupyter (4), Shell (2)

Size: 488 files, 212 scripts

Software Heritage: archived

Found in: the end of the paper

Holds: README, license file, environment (pyproject.toml, requirements.txt, setup.py), tests, continuous integration, documentation, 4 notebooks

Not found: CITATION.cff

Tools: NumPy (60 files), SciPy (21 files), pandas (6 files), anndata (4 files), Matplotlib (3 files), PyTorch (1 file), Scanpy (1 file)

Availability: 2 checks, the latest on 29 October 2026: the link answers

29 October 2026: the link answers
28 September 2026: the link answers

214 files

MACS3/Commands/__init__.py, Python, 1 line
MACS3/Commands/bdgbroadcall_cmd.py, Python, 59 lines
MACS3/Commands/bdgcmp_cmd.py, Python, 92 lines
MACS3/Commands/bdgdiff_cmd.py, Python, 107 lines
MACS3/Commands/bdgopt_cmd.py, Python, 64 lines
MACS3/Commands/bdgpeakcall_cmd.py, Python, 65 lines
MACS3/Commands/callpeak_cmd.py, Python, 436 lines
MACS3/Commands/callvar_cmd.py, Python, 368 lines
MACS3/Commands/cmbreps_cmd.py, Python, 51 lines
MACS3/Commands/filterdup_cmd.py, Python, 145 lines
MACS3/Commands/hmmratac_cmd.py, Python, 658 lines
MACS3/Commands/pileup_cmd.py, Python, 142 lines
MACS3/Commands/pileup_v2_cmd.py, Python, 80 lines
MACS3/Commands/predictd_cmd.py, Python, 131 lines
MACS3/Commands/randsample_cmd.py, Python, 131 lines
MACS3/Commands/refinepeak_cmd.py, Python, 128 lines
MACS3/IO/BAM.py, Python, 864 lines
MACS3/IO/BAMStream.py, Python, 641 lines
MACS3/IO/BedGraphIO.py, Python, 142 lines
MACS3/IO/OutputWriter.py, Python, 301 lines
MACS3/IO/Parser.py, Python, 3,391 lines
MACS3/IO/PeakIO.py, Python, 1,899 lines
MACS3/IO/__init__.py, Python, 1 line
MACS3/IO/bgzf_mt.c, C, 414 lines
MACS3/IO/bgzf_mt.h, C/C++, 83 lines
MACS3/IO/libdeflate/common_defs.h, C/C++, 735 lines
MACS3/IO/libdeflate/lib/arm/cpu_features.c, C, 292 lines
MACS3/IO/libdeflate/lib/arm/cpu_features.h, C/C++, 214 lines
MACS3/IO/libdeflate/lib/arm/crc32_impl.h, C/C++, 594 lines
MACS3/IO/libdeflate/lib/arm/crc32_pmull_helpers.h, C/C++, 156 lines
MACS3/IO/libdeflate/lib/arm/crc32_pmull_wide.h, C/C++, 226 lines
MACS3/IO/libdeflate/lib/cpu_features_common.h, C/C++, 93 lines
MACS3/IO/libdeflate/lib/crc32.c, C, 262 lines
MACS3/IO/libdeflate/lib/crc32_multipliers.h, C/C++, 375 lines
MACS3/IO/libdeflate/lib/crc32_tables.h, C/C++, 587 lines
MACS3/IO/libdeflate/lib/decompress_template.h, C/C++, 777 lines
MACS3/IO/libdeflate/lib/deflate_constants.h, C/C++, 56 lines
MACS3/IO/libdeflate/lib/deflate_decompress.c, C, 1,208 lines
MACS3/IO/libdeflate/lib/lib_common.h, C/C++, 106 lines
MACS3/IO/libdeflate/lib/utils.c, C, 141 lines
MACS3/IO/libdeflate/lib/x86/cpu_features.c, C, 213 lines
MACS3/IO/libdeflate/lib/x86/cpu_features.h, C/C++, 170 lines
MACS3/IO/libdeflate/lib/x86/crc32_impl.h, C/C++, 160 lines
MACS3/IO/libdeflate/lib/x86/crc32_pclmul_template.h, C/C++, 424 lines
MACS3/IO/libdeflate/lib/x86/decompress_impl.h, C/C++, 57 lines
MACS3/IO/libdeflate/libdeflate.h, C/C++, 412 lines
MACS3/Signal/BedGraph.py, Python, 2,648 lines
MACS3/Signal/CallPeakUnit.py, Python, 3,965 lines
MACS3/Signal/CallerExecution.py, Python, 214 lines
MACS3/Signal/CallerStorage.py, Python, 215 lines
MACS3/Signal/FixWidthTrack.py, Python, 1,105 lines
MACS3/Signal/HMMR_EM.py, Python, 284 lines
MACS3/Signal/HMMR_HMM.py, Python, 133 lines
MACS3/Signal/HMMR_Signal_Processing.py, Python, 275 lines
MACS3/Signal/PairedEndTrack.py, Python, 3,063 lines
MACS3/Signal/PeakDetect.py, Python, 440 lines
MACS3/Signal/PeakModel.py, Python, 1,130 lines
MACS3/Signal/PeakVariants.py, Python, 401 lines
MACS3/Signal/Pileup.py, Python, 1,423 lines
MACS3/Signal/PileupV2.py, Python, 1,441 lines
MACS3/Signal/PosReadsInfo.py, Python, 669 lines
MACS3/Signal/Prob.py, Python, 1,332 lines
MACS3/Signal/RACollection.py, Python, 905 lines
MACS3/Signal/ReadAlignment.py, Python, 539 lines
MACS3/Signal/Region.py, Python, 617 lines
MACS3/Signal/ScoreTrack.py, Python, 1,973 lines
MACS3/Signal/SignalProcessing.py, Python, 367 lines
MACS3/Signal/UnitigRACollection.py, Python, 323 lines
MACS3/Signal/VariantStat.py, Python, 548 lines
MACS3/Signal/__init__.py, Python, 1 line
MACS3/Signal/cPosValCalculation.c, C, 520 lines
MACS3/Signal/cPosValCalculation.h, C/C++, 41 lines
MACS3/Signal/swalign.c, C, 358 lines
MACS3/Signal/swalign.h, C/C++, 82 lines
MACS3/Utilities/Chromosome.py, Python, 21 lines
MACS3/Utilities/Constants.py, Python, 14 lines
MACS3/Utilities/Execution.py, Python, 261 lines
MACS3/Utilities/Logger.py, Python, 34 lines
MACS3/Utilities/OptValidator.py, Python, 846 lines
MACS3/Utilities/Performance.py, Python, 81 lines
MACS3/Utilities/Threads.py, Python, 99 lines
MACS3/Utilities/__init__.py, Python, 1 line
MACS3/__init__.py, Python, 1 line
MACS3/fermi-lite/bfc.c, C, 683 lines
MACS3/fermi-lite/bseq.c, C, 61 lines
MACS3/fermi-lite/bubble.c, C, 366 lines
MACS3/fermi-lite/example.c, C, 50 lines
MACS3/fermi-lite/fml.h, C/C++, 197 lines
MACS3/fermi-lite/htab.c, C, 132 lines
MACS3/fermi-lite/htab.h, C/C++, 23 lines
MACS3/fermi-lite/internal.h, C/C++, 21 lines
MACS3/fermi-lite/khash.h, C/C++, 614 lines
MACS3/fermi-lite/kmer.h, C/C++, 106 lines
MACS3/fermi-lite/kseq.h, C/C++, 248 lines
MACS3/fermi-lite/ksort.h, C/C++, 309 lines
MACS3/fermi-lite/kstring.h, C/C++, 169 lines
MACS3/fermi-lite/ksw.c, C, 359 lines
MACS3/fermi-lite/ksw.h, C/C++, 71 lines
MACS3/fermi-lite/kthread.c, C, 67 lines
MACS3/fermi-lite/kvec.h, C/C++, 110 lines
MACS3/fermi-lite/mag.c, C, 620 lines
MACS3/fermi-lite/mag.h, C/C++, 69 lines
MACS3/fermi-lite/misc.c, C, 294 lines
MACS3/fermi-lite/mrope.c, C, 307 lines
MACS3/fermi-lite/mrope.h, C/C++, 114 lines
MACS3/fermi-lite/rld0.c, C, 489 lines
MACS3/fermi-lite/rld0.h, C/C++, 137 lines
MACS3/fermi-lite/rle.c, C, 191 lines
MACS3/fermi-lite/rle.h, C/C++, 78 lines
MACS3/fermi-lite/rope.c, C, 219 lines
MACS3/fermi-lite/rope.h, C/C++, 54 lines
MACS3/fermi-lite/unitig.c, C, 455 lines
docs/source/conf.py, Python, 116 lines
notebooks/10k-PBMC-test/macs3-scATAC-pbmc-10k.ipynb, Jupyter, 392 lines
notebooks/500-PBMC-test/anndata_implemetation_dev.ipynb, Jupyter, 320 lines
notebooks/500-PBMC-test/macs3-scATAC-pbmc-500-anndata.ipynb, Jupyter, 447 lines
notebooks/500-PBMC-test/macs3-scATAC-pbmc-500.ipynb, Jupyter, 367 lines
scripts/benchmark_performance.py, Python, 421 lines
scripts/benchmark_pileup_mlx.py, Python, 270 lines
scripts/benchmark_scoretrack_torch.py, Python, 93 lines
scripts/build_docs.py, Python, 112 lines
scripts/check_native_distribution.py, Python, 83 lines
scripts/performance_fixtures.py, Python, 109 lines
scripts/performance_probe.py, Python, 230 lines
scripts/run_macs3_release_benchmark.sh, Shell, 223 lines
scripts/run_macs_version_survey.sh, Shell, 263 lines
scripts/run_native_regressions.py, Python, 50 lines
scripts/summarize_macs3_release_benchmark.py, Python, 218 lines
scripts/summarize_macs_version_survey.py, Python, 108 lines
setup.py, Python, 217 lines
test/chromosome_batching_probe.py, Python, 275 lines
test/conftest.py, Python, 362 lines
test/execution_probe.py, Python, 269 lines
test/jaccard.py, Python, 50 lines
test/native_probe.py, Python, 200 lines
test/native_sysfs.c, C, 53 lines
test/peakmodel_alloc.h, C/C++, 95 lines
test/peakmodel_alloc_runner.py, Python, 105 lines
test/test_BAMBAI.py, Python, 765 lines
test/test_BedGraph.py, Python, 1,324 lines
test/test_BedGraphIO.py, Python, 387 lines
test/test_CallPeakUnit.py, Python, 1,628 lines
test/test_CallPeakUnit_backend.py, Python, 182 lines
test/test_CallPeakUnit_concurrency.py, Python, 168 lines
test/test_Constants.py, Python, 172 lines
test/test_Execution.py, Python, 223 lines
test/test_Execution_paths.py, Python, 320 lines
test/test_FixWidthTrack.py, Python, 795 lines
test/test_HMMR_EM.py, Python, 443 lines
test/test_HMMR_HMM.py, Python, 668 lines
test/test_HMMR_Signal_Processing.py, Python, 605 lines
test/test_HMMR_poisson.py, Python, 89 lines
test/test_Logger.py, Python, 350 lines
test/test_OptValidator.py, Python, 1,145 lines
test/test_OutputWriter.py, Python, 271 lines
test/test_PairedEndTrack.py, Python, 1,461 lines
test/test_Parser.py, Python, 1,427 lines
test/test_Parser_bam_truncation.py, Python, 210 lines
test/test_Parser_bampe_validation.py, Python, 159 lines
test/test_Parser_frag_eof.py, Python, 254 lines
test/test_Parser_imports.py, Python, 43 lines
test/test_Parser_text_eof.py, Python, 206 lines
test/test_PeakDetect.py, Python, 952 lines
test/test_PeakIO.py, Python, 1,076 lines
test/test_PeakModel.py, Python, 580 lines
test/test_PeakModel_allocation.py, Python, 112 lines
test/test_PeakVariants.py, Python, 347 lines
test/test_Performance.py, Python, 186 lines
test/test_Pileup.py, Python, 1,009 lines
test/test_PileupV2.py, Python, 352 lines
test/test_PosReadsInfo.py, Python, 668 lines
test/test_Prob.py, Python, 931 lines
test/test_Prob_concurrency.py, Python, 247 lines
test/test_RACollection.py, Python, 428 lines
test/test_ReadAlignment.py, Python, 433 lines
test/test_Region.py, Python, 637 lines
test/test_ScoreTrack.py, Python, 1,312 lines
test/test_SignalProcessing.py, Python, 568 lines
test/test_UnitigRACollection.py, Python, 227 lines
test/test_VariantStat.py, Python, 399 lines
test/test_bam_short.py, Python, 165 lines
test/test_bdgbroadcall_cmd.py, Python, 416 lines
test/test_bdgcmp_cmd.py, Python, 671 lines
test/test_bdgdiff_cmd.py, Python, 582 lines
test/test_bdgopt_cmd.py, Python, 344 lines
test/test_bdgpeakcall_cmd.py, Python, 700 lines
test/test_caller_ownership.py, Python, 86 lines
test/test_callpeak_cmd.py, Python, 2,675 lines
test/test_callpeak_local_windows.py, Python, 173 lines
test/test_callvar_cmd.py, Python, 1,054 lines
test/test_chromosome_batching.py, Python, 129 lines
test/test_chromosome_names.py, Python, 139 lines
test/test_cmbreps_cmd.py, Python, 381 lines
test/test_downsample_empty.py, Python, 177 lines
test/test_filter_dup_singletons.py, Python, 104 lines
test/test_filterdup_cmd.py, Python, 1,028 lines
test/test_hmmratac_cmd.py, Python, 1,993 lines
test/test_macs3.py, Python, 412 lines
test/test_native_allocator.py, Python, 57 lines
test/test_native_cli.py, Python, 98 lines
test/test_native_compatibility.py, Python, 78 lines
test/test_native_streams.py, Python, 193 lines
test/test_online.py, Python, 42 lines
test/test_performance_benchmark.py, Python, 196 lines
test/test_pileup_cmd.py, Python, 969 lines
test/test_pileup_lifecycle.py, Python, 331 lines
test/test_predictd_cmd.py, Python, 759 lines
test/test_randsample_cmd.py, Python, 770 lines
test/test_refinepeak_cmd.py, Python, 531 lines
test/test_sam_reverse.py, Python, 111 lines
test/test_singleton_frag.py, Python, 146 lines
test/test_thread_lifecycle.py, Python, 236 lines
LICENSE, License, 28 lines
README.md, Text, 92 lines

At the source: github.com/macs3-project/MACS

ippas/ifpan-janrod-spatial

License: none: the authors keep all their rights

State: the link answers, verified on 28 September 2026

Evidence: files inventoried

Commit: 03f0a59895f28cd124562d4e07b397f41684a177, 1 September 2026

Languages: R (204), Python (23), Shell (8)

Size: 286 files, 235 scripts

Software Heritage: not archived

Found in: the end of the paper

Holds: README, environment (.devcontainer/devcontainer.json, preprocessing/dockerfiles/Dockerfile.peaks, preprocessing/dockerfiles/Dockerfile.r4.0.3-seurat4-package-version-spatial, preprocessing/dockerfiles/Dockerfile.r4.0.3-seurat4-package-version-spatial-update, preprocessing/dockerfiles/Dockerfile.r4.0.3-seurat4-shiny, preprocessing/dockerfiles/Dockerfile.r4.0.3-seurat4-spatial, preprocessing/dockerfiles/Dockerfile.r4.3.0-seurat5, preprocessing/dockerfiles/Dockerfile.rstudio, preprocessing/dockerfiles/Dockerfile.shiny)

Not found: license file, CITATION.cff, tests, continuous integration, documentation

Tools: tidyverse (81 files), circlize (28 files), ComplexHeatmap (28 files), pandas (21 files), patchwork (17 files), scikit-learn (15 files), Matplotlib (12 files), NumPy (12 files), edgeR (11 files), ggplot2 (11 files), anndata (6 files), Seurat (4 files), BEDTools (3 files), SciPy (3 files), igraph (2 files), limma (2 files), pysam (2 files), SAMtools (2 files), seaborn (2 files), cowplot (1 file), data.table (1 file), DESeq2 (1 file), psych (1 file), reshape2 (1 file), Scanpy (1 file)

Availability: 1 check, the latest on 28 September 2026: the link answers

28 September 2026: the link answers

236 files

preprocessing/bed2gtf-spaceranger.py, Python, 91 lines
preprocessing/clozapine/clozapine-analysis-half.R, R, 140 lines
preprocessing/clozapine/clozapine-analysis.R, R, 140 lines
preprocessing/clozapine/supplementaryAnalysis_paper_03.12.2025.R, R, 66 lines, 1 match
preprocessing/clozapine/umap_table_review_08.01.2026/tableXLSX_markers_ClozapineRisperidone.R, R, 223 lines
preprocessing/clozapine/umap_table_review_08.01.2026/tableXLSX_numberCellsPerCluster_ClozapineRisperidone.R, R, 100 lines
preprocessing/clozapine/umap_table_review_08.01.2026/umap_supplementary_08.01.2026.R, R, 50 lines
preprocessing/functions/compute_cluster_sum_mean_v3.R, R, 438 lines
preprocessing/functions/enrichr.R, R, 57 lines
preprocessing/functions/functions-shiny/selected_clusters.R, R, 15 lines
preprocessing/functions/functions-spatial-data.R, R, 765 lines, 1 match
preprocessing/functions/generate_global_heatmap/generate_global_heatmap_07.04.2026.R, R, 326 lines
preprocessing/functions/generate_global_heatmap/generate_global_heatmap_18.12.2025.R, R, 960 lines
preprocessing/functions/global-summary-espression.R, R, 119 lines
preprocessing/functions/heatmap-functions/plot_gene_heatmap_from_bundle.R, R, 1,274 lines
preprocessing/functions/heatmap-functions/plot_gene_heatmap_group_deltas_from_bundle.R, R, 223 lines
preprocessing/functions/heatmap-functions/plot_gene_heatmap_group_means_from_bundle.R, R, 209 lines
preprocessing/functions/heatmap-functions/plot_gene_heatmap_group_ratios_from_bundle.R, R, 245 lines
preprocessing/functions/list-genes.R, R, 308 lines
preprocessing/functions/permutation-test.R, R, 159 lines
preprocessing/functions/shiny-functions.R, R, 67 lines
preprocessing/functions/spatial-generate-global-heatmap.R, R, 530 lines
preprocessing/functions/spatial_cluster_expression_heatmap-v1.15.R, R, 169 lines
preprocessing/functions/spatial_cluster_select.R, R, 84 lines
preprocessing/functions/statistics-functions-v2.R, R, 520 lines, 1 match
preprocessing/functions/statistics-functions.R, R, 665 lines
preprocessing/functions/statistics-functions/compute_data_summary_v3.R, R, 75 lines
preprocessing/functions/statistics-functions/edger_pseudobuld_twofactor_generic.R, R, 181 lines
preprocessing/functions/statistics-functions/edger_twofactor_anova_and_posthoc.R, R, 639 lines
preprocessing/functions/statistics-functions/edger_twofactor_anova_and_posthoc_v2.R, R, 273 lines
preprocessing/functions/statistics-functions/run_edger_twoFactors_perClusters/run_edger_twoFactors_perClusters.R, R, 1,096 lines
preprocessing/functions/statistics-functions/run_edger_twoFactors_perClusters/run_edger_twoFactors_perClusters_v2.R, R, 1,030 lines
preprocessing/functions/statistics-functions/run_edger_twofactor_for_cluster.R, R, 137 lines
preprocessing/functions/statistics-functions/run_edger_twofactor_for_clusters_v2.R, R, 323 lines
preprocessing/functions/statistics-functions/statistics-function-v5.R, R, 309 lines
preprocessing/functions/statistics-functions/statistics-functions-v3.R, R, 754 lines
preprocessing/functions/statistics-functions/summarize_and_test_v2.R, R, 79 lines
preprocessing/functions/test-function-statistics.R, R, 214 lines
preprocessing/functions/umap_feature_expression_plot.R, R, 267 lines, 1 match
preprocessing/functions/umi-per-spot.R, R, 72 lines
preprocessing/functions/visualization-functions.R, R, 957 lines
preprocessing/functions/write_cluster_list_to_xlsx.R, R, 13 lines
preprocessing/functions/zero-nonzero-ratio.R, R, 168 lines
preprocessing/installing-require-packages.R, R, 28 lines
preprocessing/ldopa/ldopa-analysis.R, R, 314 lines
preprocessing/ldopa/ldopa-permutation-fdr.R, R, 139 lines
preprocessing/ldopa/test-umap-single-gene.R, R, 1 line
preprocessing/old-scripts/analysis-data-normalize.R, R, 143 lines
preprocessing/old-scripts/analysis-data-seurat.R, R, 142 lines
preprocessing/old-scripts/deseq-test-analysis.R, R, 477 lines, 1 match
preprocessing/old-scripts/generate-raport.R, R, 89 lines
preprocessing/old-scripts/old-code.R, R, 324 lines
preprocessing/old-scripts/preparation-functions.R, R, 1,041 lines
preprocessing/old-scripts/preparation-visualization.R, R, 117 lines
preprocessing/old-scripts/prepare-annotate-peaks.sh, Shell, 167 lines
preprocessing/old-scripts/read-data.R, R, 73 lines
preprocessing/old-scripts/reduction-peaks.R, R, 584 lines, 1 match
preprocessing/old-scripts/spaceranger-analysis.sh, Shell, 91 lines
preprocessing/old-scripts/statistics.R, R, 127 lines
preprocessing/old-scripts/visualization-seurat.R, R, 110 lines
preprocessing/prepare-annotate-peaks-v2.sh, Shell, 150 lines
preprocessing/prepare-annotate-peaks.sh, Shell, 167 lines
preprocessing/python/scripts/extract-coverage-for-genes-test.py, Python, 186 lines
preprocessing/python/src/__init__.py, Python, 1 line
preprocessing/python/src/bam_coverage_utils.py, Python, 152 lines
preprocessing/python/src/mouse_annotations_downloader.py, Python, 56 lines
preprocessing/python/src/plotting_functions.py, Python, 317 lines
preprocessing/python/src/workflow_utils.py, Python, 29 lines
preprocessing/pz-1190/pz-1190-analysis-half.R, R, 178 lines
preprocessing/pz-1190/pz-1190-analysis.R, R, 178 lines
preprocessing/reduction-peaks.R, R, 584 lines
preprocessing/risperidone-3q29/add-hoc-analysis/ris3q29-investigate-samples.R, R, 61 lines
preprocessing/risperidone-3q29/add-hoc-analysis/ris3q29-meanEgr3Usp48.R, R, 35 lines
preprocessing/risperidone-3q29/add-hoc-analysis/ris3q29-meanGenesPerSample.R, R, 50 lines
preprocessing/risperidone-3q29/add-hoc-analysis/ris3q29-nr3.R, R, 229 lines
preprocessing/risperidone-3q29/add-hoc-analysis/ris3q29-umap-25samples.R, R, 100 lines
preprocessing/risperidone-3q29/clustering-spatial-continuity/01_evaluateClusteringSpatialContinuity_PAS_CHAOS_ASW.R, R, 1,475 lines
preprocessing/risperidone-3q29/debug-summary-data-cluster4.R, R, 183 lines
preprocessing/risperidone-3q29/edgeR/edger_cross_cell_contrasts_by_cluster_16.06.2026.R, R, 728 lines
preprocessing/risperidone-3q29/edgeR/edger_cross_cell_contrasts_by_cluster_29.06.2026.R, R, 751 lines
preprocessing/risperidone-3q29/edgeR/investigation_logFC_edger.R, R, 29 lines
preprocessing/risperidone-3q29/edgeR/prepare_logCPM_per_sample_for_clusters.R, R, 351 lines
preprocessing/risperidone-3q29/edgeR/pseudobulk_edgeR_n25Samples_min15Spots_02.07.2026.R, R, 687 lines
preprocessing/risperidone-3q29/edgeR/ris3q29_edgerInteraction_test.R, R, 301 lines
preprocessing/risperidone-3q29/edgeR/ris3q29_edgerMarginaProportional_permutationFDRInteraction.R, R, 444 lines
preprocessing/risperidone-3q29/edgeR/ris3q29_edger_MarginalProportional.R, R, 626 lines
preprocessing/risperidone-3q29/edgeR/ris3q29_edger_scatterplotLog2FC.R, R, 164 lines
preprocessing/risperidone-3q29/edgeR/ris3q29_prepareExpressionByClusters_29.06.2026.R, R, 594 lines
preprocessing/risperidone-3q29/edgeR/ris3q29_visSumQN_heatmap.R, R, 183 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-test.R, R, 81 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.10.R, R, 147 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.11.R, R, 159 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.12.R, R, 170 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.13.R, R, 152 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.14.R, R, 188 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.3.R, R, 127 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.4.R, R, 130 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.6.R, R, 134 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.7.R, R, 136 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func-v1.8.R, R, 143 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-func1.5.R, R, 133 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-function-v1.1.R, R, 142 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-complexheatmap-function-v1.R, R, 113 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-globalHeatmap-test.R, R, 263 lines
preprocessing/risperidone-3q29/heatmap/ris3q29-globalSummary-v2.R, R, 321 lines
preprocessing/risperidone-3q29/interaction-heatmap-16.10.2025/plot_heatmap_zscoreSalineType_customDist.R, R, 442 lines
preprocessing/risperidone-3q29/ris3q29-analysis-seurat-v2.R, R, 295 lines
preprocessing/risperidone-3q29/ris3q29-analysis-seurat.R, R, 333 lines
preprocessing/risperidone-3q29/ris3q29-complexheatmap.R, R, 106 lines
preprocessing/risperidone-3q29/ris3q29-deletion-genes-heatmap.R, R, 116 lines
preprocessing/risperidone-3q29/ris3q29-edgerStatistics.R, R, 389 lines
preprocessing/risperidone-3q29/ris3q29-find-markers.R, R, 61 lines
preprocessing/risperidone-3q29/ris3q29-heatmap-dev2.R, R, 159 lines
preprocessing/risperidone-3q29/ris3q29-statistcs.R, R, 191 lines
preprocessing/risperidone-3q29/ris3q29-statistics-v3.R, R, 186 lines
preprocessing/risperidone-3q29/ris3q29-visualization-results-test.R, R, 120 lines
preprocessing/risperidone-3q29/ris3q29_preapreMeanExpressionPersSampleMin20spots_09.06.2026.R, R, 336 lines
preprocessing/risperidone-3q29/ris3q39-heatmap.R, R, 246 lines
preprocessing/risperidone-3q29/sandbox/sandbox-15.10.2025/heatmap-interaction-zscoreSalinePerGenotype.R, R, 104 lines
preprocessing/risperidone-3q29/sandbox/sandbox-15.10.2025/heatmap-test-zscore.R, R, 46 lines
preprocessing/risperidone-3q29/sandbox/sandbox-15.10.2025/heatmap-test-zscore_v2.R, R, 101 lines
preprocessing/risperidone-3q29/sandbox/sandbox-15.10.2025/heatmap-test-zscore_v3-wtwtSalienZscore.R, R, 113 lines
preprocessing/risperidone-3q29/sandbox/sandbox-15.10.2025/heatmap-test-zsocre-allSamplesHeatmap.R, R, 58 lines
preprocessing/risperidone-3q29/sandbox/sandbox-15.10.2025/plot_gene_heatmap_group_means_refZscore_from_bundle.R, R, 251 lines
preprocessing/risperidone-3q29/summary-statistics-debug/compute-data-summary-debug.R, R, 170 lines
preprocessing/risperidone-3q29/summary-statistics-debug/summarize_and_test-debug-v2.R, R, 138 lines
preprocessing/risperidone-3q29/summary-statistics-debug/summarize_and_test-debug.R, R, 155 lines
preprocessing/risperidone-3q29/summary_clusters/summarize_cluster_barcodes_per_sample.R, R, 40 lines
preprocessing/risperidone/customize-clusters.R, R, 139 lines
preprocessing/risperidone/function-statistics.R, R, 102 lines
preprocessing/risperidone/gene-count-per-spot.R, R, 104 lines
preprocessing/risperidone/generate-raport.R, R, 89 lines
preprocessing/risperidone/jackcraig-prepare-spatialdata.R, R, 187 lines
preprocessing/risperidone/ris-umap-genes.R, R, 67 lines, 1 match
preprocessing/risperidone/ris_permutataion_minSpot15_16.03.2026.R, R, 762 lines
preprocessing/risperidone/risperidone-analysis-half-seurat5.R, R, 201 lines
preprocessing/risperidone/risperidone-analysis.R, R, 149 lines
preprocessing/risperidone/risperidone-half-analysis-defaultReference_17.03.2026.R, R, 766 lines
preprocessing/risperidone/risperidone-half-analysis.R, R, 320 lines
preprocessing/risperidone/risperidone-half-statistics-spotThreshold15-11.02.2026.R, R, 188 lines
preprocessing/risperidone/risperidone-half-statistics.R, R, 101 lines
preprocessing/risperidone/risperidone-median-transcript-per-spot.R, R, 2 lines
preprocessing/risperidone/risperidone_findMarkers_12.02.2026.R, R, 135 lines
preprocessing/risperidone/spatial-cluster-stability/prepareData_toSilhouette_v1_2026.R, R, 69 lines
preprocessing/risperidone/spatial-cluster-stability/run_sdmbench_chaos_pas/run_sdmbench_chaos_pas_v1_27.04.2026.py, Python, 169 lines
preprocessing/risperidone/spatial-cluster-stability/run_sdmbench_chaos_pas/run_sdmbench_chaos_pas_v2_27.04.2026.py, Python, 195 lines
preprocessing/risperidone/spatial-cluster-stability/run_sdmbench_chaos_pas/run_sdmbench_chaos_pas_v3_27.04.2026.py, Python, 192 lines
preprocessing/risperidone/spatial-cluster-stability/run_sdmbench_chaos_pas/run_sdmbench_chaos_pas_v4_27.04.2026.py, Python, 229 lines
preprocessing/risperidone/spatial-cluster-stability/run_sdmbench_chaos_pas/run_sdmbench_chaos_pas_v5_27.04.2026.py, Python, 265 lines
preprocessing/risperidone/spatial-cluster-stability/run_sdmbench_chaos_pas/run_sdmbench_chaos_pas_v6_27.04.2026.py, Python, 230 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_resolution_compare_0.4_vs_0.85_FAST_v1_27.04.2026.py, Python, 439 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v1_27.04.2026.py, Python, 128 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v2_27.04.2026.py, Python, 148 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v3_27.04.2026.py, Python, 152 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v4_27.04.2026.py, Python, 160 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v5_27.04.2026.py, Python, 166 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v6_27.04.2026.py, Python, 255 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v7_27.04.2026.py, Python, 221 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v8_27.04.2026.py, Python, 267 lines
preprocessing/risperidone/spatial-cluster-stability/run_silhouette_analysis/run_silhouette_analysis_v9_27.04.2026.py, Python, 322 lines
preprocessing/risperidone/spatial-cluster-stability/sandbox/ris-spatial-cluster-stability_v1_27.04.2026.R, R, 121 lines
preprocessing/risperidone/spatial-cluster-stability/sandbox/ris-spatial-cluster-stability_v2_27.04.2026.R, R, 38 lines
preprocessing/risperidone/spatial-cluster-stability/sandbox/ris-spatial-cluster-stability_v3_08.05.2026.R, R, 101 lines
preprocessing/shiny-app/clusters-testing.R, R, 66 lines
preprocessing/shiny-app/debugging-shiny-external.R, R, 46 lines
preprocessing/shiny-app/debugging-shiny-inner.R, R, 45 lines
preprocessing/shiny-app/shiny-app-plot-test1.R, R, 94 lines
preprocessing/shiny-app/shiny-app-plot-test2.R, R, 64 lines
preprocessing/shiny-app/shiny-app-plot-test3.R, R, 48 lines
preprocessing/shiny-app/shiny-app-plot-test4.R, R, 78 lines
preprocessing/shiny-app/shiny-app-spatial5.R, R, 326 lines
preprocessing/shiny-app/shiny-app-spatial6.R, R, 319 lines
preprocessing/shiny-app/shiny-app-spatial7.R, R, 384 lines
preprocessing/shiny-app/shiny-app-spatial8.R, R, 539 lines
preprocessing/shiny-app/shiny-app-spatial9.R, R, 660 lines
preprocessing/shiny-app/shiny-app-test1.R, R, 79 lines
preprocessing/shiny-app/shiny-app-test2.R, R, 118 lines
preprocessing/shiny-app/shiny-app-test3.R, R, 232 lines
preprocessing/shiny-app/shiny-app-test4.R, R, 296 lines
preprocessing/shiny-app/shiny-spatial-external1.R, R, 312 lines
preprocessing/shiny-app/shiny-spatial-external2.R, R, 380 lines
preprocessing/shiny-app/shiny-spatial-external3.R, R, 523 lines
preprocessing/shiny-app/shiny-test-docker1.R, R, 32 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.1.R, R, 84 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.10.R, R, 923 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.11.R, R, 997 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.2.R, R, 163 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.3.R, R, 175 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.4.R, R, 218 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.5.R, R, 448 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.6.R, R, 457 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.8.R, R, 896 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.0.9.R, R, 671 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/spatial-browser-v2.1.0.R, R, 1,189 lines
preprocessing/shiny-app/spatial-browser-v2.0-dev/sptial-browser-v2.0.7.R, R, 815 lines
preprocessing/shiny-app/spatial-browser-v2.1-deploy/app.R, R, 12 lines
preprocessing/shiny-app/spatial-browser-v2.1-deploy/global.R, R, 71 lines
preprocessing/shiny-app/spatial-browser-v2.1-deploy/server.R, R, 589 lines
preprocessing/shiny-app/spatial-browser-v2.1-deploy/ui.R, R, 360 lines
preprocessing/shiny-app/spatial-browser-v2.2-deploy/app.R, R, 12 lines
preprocessing/shiny-app/spatial-browser-v2.2-deploy/global.R, R, 158 lines
preprocessing/shiny-app/spatial-browser-v2.2-deploy/server.R, R, 752 lines
preprocessing/shiny-app/spatial-browser-v2.2-deploy/ui.R, R, 421 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser1/app.R, R, 12 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser1/global.R, R, 16 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser1/server.R, R, 395 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser1/ui.R, R, 146 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser2/app.R, R, 12 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser2/global.R, R, 17 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser2/server.R, R, 455 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser2/ui.R, R, 178 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser3/app.R, R, 12 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser3/global.R, R, 18 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser3/server.R, R, 530 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser3/ui.R, R, 189 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser4/app.R, R, 12 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser4/global.R, R, 20 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser4/server.R, R, 554 lines
preprocessing/shiny-app/spatial-transcriptomics-drug-browser4/ui.R, R, 206 lines
preprocessing/spaceranger-analysis-v1.1.sh, Shell, 158 lines
preprocessing/spaceranger-analysis-v2.sh, Shell, 102 lines
preprocessing/spaceranger-analysis.sh, Shell, 103 lines
preprocessing/spaceranger-analysis2.sh, Shell, 106 lines
preprocessing/tested-scripts/development-statistics.R, R, 283 lines
preprocessing/tested-scripts/development-statistics2.R, R, 230 lines
preprocessing/tested-scripts/edger--statistics.R, R, 59 lines
preprocessing/tested-scripts/multiple-generating-png.R, R, 307 lines
preprocessing/tested-scripts/quartile-normalization-test.R, R, 250 lines
preprocessing/tested-scripts/statistics.R, R, 238 lines
preprocessing/tested-scripts/test.r, R, 55 lines
preprocessing/tested-scripts/visualization-seurat.R, R, 110 lines
preprocessing/to-remove/analysis-data-normalize.R, R, 143 lines
preprocessing/to-remove/analysis-data-seurat.R, R, 118 lines
preprocessing/to-remove/preparation-visualization.R, R, 137 lines
preprocessing/to-remove/read-data.R, R, 73 lines
README.md, Text, 91 lines

At the source: github.com/ippas/ifpan-janrod-spatial

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
447 scripts, each with its path and the digest of its content;
7 matches between paragraphs of the paper and lines of the code (method lexical-v1);
neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability statement

The RNAseq dataset generated for this study can be found in the Sequence Read Archive, https://www.ncbi.nlm.nih.gov/, under accession number PRJNA1143882.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 9 authors, 7 keywords, 79 references, 9 RRIDs.

Cite

This paper

Ziemiańska, M., Zięba, M., Radlicka-Borysewska, A., Szumiec, Ł., Gołda, S., Borczyk, M., Piechota, M., Korostyński, M., & Rodriguez Parkitna, J. (2026). Risperidone regulates the expression of schizophrenia-related genes in the forebrain of adult male mice. Frontiers in molecular neuroscience, 19, 1844705. https://doi.org/10.3389/fnmol.2026.1844705

BibTeX

@article{ziemianska2026risperidone, author = {Ziemiańska, Magdalena and Zięba, Mateusz and Radlicka-Borysewska, Anna and Szumiec, Łukasz and Gołda, Sławomir and Borczyk, Małgorzata and Piechota, Marcin and Korostyński, Michał and Rodriguez Parkitna, Jan}, title = {{Risperidone regulates the expression of schizophrenia-related genes in the forebrain of adult male mice}}, journal = {Frontiers in molecular neuroscience}, year = {2026}, month = may, volume = {19}, pages = {1844705}, publisher = {Frontiers Media SA}, issn = {1662-5099}, doi = {10.3389/fnmol.2026.1844705}, url = {https://doi.org/10.3389/fnmol.2026.1844705}, pmid = {42293048}, pmcid = {PMC13260059} }

RIS

TY - JOUR AU - Ziemiańska, Magdalena AU - Zięba, Mateusz AU - Radlicka-Borysewska, Anna AU - Szumiec, Łukasz AU - Gołda, Sławomir AU - Borczyk, Małgorzata AU - Piechota, Marcin AU - Korostyński, Michał AU - Rodriguez Parkitna, Jan TI - Risperidone regulates the expression of schizophrenia-related genes in the forebrain of adult male mice T2 - Frontiers in molecular neuroscience J2 - Front Mol Neurosci PY - 2026 DA - 2026/05/29 VL - 19 SP - 1844705 SN - 1662-5099 PB - Frontiers Media SA DO - 10.3389/fnmol.2026.1844705 UR - https://doi.org/10.3389/fnmol.2026.1844705 LA - en ER -

CSL-JSON

{ "id": "10.3389/fnmol.2026.1844705", "type": "article-journal", "title": "Risperidone regulates the expression of schizophrenia-related genes in the forebrain of adult male mice", "container-title": "Frontiers in molecular neuroscience", "author": [ { "family": "Ziemiańska", "given": "Magdalena" }, { "family": "Zięba", "given": "Mateusz" }, { "family": "Radlicka-Borysewska", "given": "Anna" }, { "family": "Szumiec", "given": "Łukasz" }, { "family": "Gołda", "given": "Sławomir" }, { "family": "Borczyk", "given": "Małgorzata" }, { "family": "Piechota", "given": "Marcin" }, { "family": "Korostyński", "given": "Michał" }, { "family": "Rodriguez Parkitna", "given": "Jan" } ], "container-title-short": "Front Mol Neurosci", "volume": "19", "page": "1844705", "DOI": "10.3389/fnmol.2026.1844705", "PMID": "42293048", "PMCID": "PMC13260059", "ISSN": "1662-5099", "publisher": "Frontiers Media SA", "URL": "https://doi.org/10.3389/fnmol.2026.1844705", "language": "en", "issued": { "date-parts": [ [ 2026, 5, 29 ] ] } }

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.15252/msb.202211080 [code]: Vesalius: high-resolution in silico anatomization of spatial transcriptomic data using image analysis.
Journal: Molecular systems biology
In common: edgeR, anndata, limma, 19 other tools, genetics / omics, mouse, 3 references
[2] doi:10.1016/j.celrep.2025.116877 [code]: Spatially resolved molecular sex differences at single-cell resolution in the adult human ventromedial and arcuate hypothalamus.
Journal: Cell reports
In common: edgeR, anndata, limma, 18 other tools, genetics / omics, cellular / molecular, 3 references
[3] doi:10.1038/s41467-026-76675-1 [code]: Long-read proteogenomic atlas of human neuronal differentiation reveals isoform diversity informing neurodevelopmental risk mechanisms.
Journal: Nature communications
In common: pysam, BEDTools, edgeR, 18 other tools, genetics / omics
[4] doi:10.1016/j.xgen.2023.100399 [code]: Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons.
Journal: Cell genomics
In common: pysam, edgeR, SAMtools, 16 other tools, schizophrenia / psychosis, genetics / omics, cellular / molecular, 1 reference
[5] doi:10.1126/sciadv.adq2290 [code]: Contrasting genetic predisposition and diagnosis in psychiatric disorders: A multi-omic single-nucleus analysis of the human OFC.
Journal: Science advances
In common: edgeR, anndata, circlize, 16 other tools, schizophrenia / psychosis, genetics / omics, 2 references
[6] doi:10.1038/s41593-025-02022-0 [code]: An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.
Journal: Nature neuroscience
In common: edgeR, anndata, limma, 17 other tools, genetics / omics, 2 references
[7] doi:10.1016/j.isci.2023.106701 [code]: Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia.
Journal: iScience
In common: edgeR, SAMtools, limma, 13 other tools, schizophrenia / psychosis, genetics / omics, cellular / molecular, 4 references
[8] doi:10.1186/s13059-026-04177-w [code]: Genomic sequence evolution underlying human neocortical interareal diversification.
Journal: Genome biology
In common: pysam, BEDTools, SAMtools, 16 other tools, genetics / omics, mouse, cellular / molecular
[9] doi:10.1038/s41467-026-69944-6 [code]: Multi-modal dissection of cell-type specific TDP-43 pathology in the motor cortex.
Journal: Nature communications
In common: pysam, BEDTools, SAMtools, 15 other tools, genetics / omics, 1 reference
[10] doi:10.1093/bib/bbaf316 [code]: TriCLFF: a multi-modal feature fusion framework using contrastive learning for spatial domain identification.
Journal: Briefings in bioinformatics
In common: edgeR, SAMtools, anndata, 15 other tools, genetics / omics, mouse, 2 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Add the badge to the code's README

If you are an author or a maintainer of this paper's code, you can add this badge. It says what OSCR knows of the paper (its code, its validated tracing map) and links the code to this page. Paste one of these snippets under the README's title. Keep the two marks around it, so that the badge can be replaced in place and is never added twice. OSCR changes nothing in your repository.

Markdown

<!-- oscr-badge:start -->
[![OSCR](https://openscicode.org/badge/doi/10.3389/fnmol.2026.1844705.svg)](https://openscicode.org/badge/doi/10.3389/fnmol.2026.1844705)
<!-- oscr-badge:end -->

reStructuredText

.. oscr-badge:start

.. image:: https://openscicode.org/badge/doi/10.3389/fnmol.2026.1844705.svg
   :target: https://openscicode.org/badge/doi/10.3389/fnmol.2026.1844705
   :alt: OSCR

.. oscr-badge:end

HTML

<!-- oscr-badge:start -->
<a href="https://openscicode.org/badge/doi/10.3389/fnmol.2026.1844705"><img src="https://openscicode.org/badge/doi/10.3389/fnmol.2026.1844705.svg" alt="OSCR"></a>
<!-- oscr-badge:end -->

On GitHub, open the README, choose Edit (the pencil), paste the snippet under the title, then "Commit changes".

If you choose to, you can have the badge kept up to date for you, with oscr badge --write from the command line or with the GitHub Action in your repository's workflows. Every other form and option (a card, AsciiDoc, LaTeX, shields.io) is on the badge page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: code errors and mismatches between the code and the paper about this paper and its code, from readers and its authors, beside the paper and its tracing map.

Report a mismatch between the code and the paper · Report a code error (signed in)

Reproductions: reports from readers who ran the authors' code and did not get the paper's result, what they ran, with which environment, commit and data.

Report a reproduction failure (signed in)

Versions of its code: the releases of its code tied to a version of this paper (the preprint, the accepted manuscript, the version of record…), each with the tracing map versioned with it.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.