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A single-cell atlas of alternative wing development in two hemipteran species.

Code ↔ Paper

6 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 6 matches · 5 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Correlation analysis of bulk RNA-seq and scRNA-seq ↔ scripts/02_Bulk_vs_PseudoBulk_Correlation.R, the whole file · a weak match · score 0.81 · pseudo bulk, Bulk RNA seq, bulk expression, correlation, scRNA, Pearson
  2. [2] § Results › Single-cell atlas of SW- and LW-destined wing buds in the firebug ↔ scripts/04_TF_Regulon_Activity_Visualization.R, the whole file · a weak match · score 0.80 · neuron cells, glial cells, muscle cells, tracheal cells, epithelial cells, single cell
  3. [3] § Results › Evolutionary conservation of cell types between the firebug and the planthopper ↔ scripts/04_TF_Regulon_Activity_Visualization.R, the whole file · a weak match · score 0.76 · neuron cells, glial cells, muscle cells, tracheal cells, epithelial cells, homologous
  4. [4] § Results › Cell composition of SW- and LW-destined wings ↔ scripts/02_Bulk_vs_PseudoBulk_Correlation.R, the whole file · a weak match · score 0.62 · pseudo bulk, bulk RNA seq, scRNA, Pearson
  5. [5] § Methods › scRNA-seq data analysis ↔ scripts/01_Cross_Species_Comparison_HFS_SHC.R, lines 47–97 · score 0.58 · FindNeighbors, UMAP, Seurat, clustering
  6. [6] § Methods › Correlation analysis of bulk RNA-seq and scRNA-seq ↔ scripts/03_Marker_Gene_Heatmap_Bulk.R, the whole file · a weak match · score 0.56 · Bulk RNA seq, bulk expression, log2, transformed, heatmap, cells

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

R · 44 lines · 1.9 KB · MIT · 2 matches

  1. # ==========================================================================
  2. # Script: 02_Bulk_vs_PseudoBulk_Correlation.R
  3. # Purpose: Correlation between Bulk RNA-seq and Pseudo-bulk from scRNA-seq
  4. # ==========================================================================
  5. library(ggplot2)
  6. library(dplyr)
  7. library(readr)
  8. # 1. Load Data (Using relative paths)
  9. bulk_expr <- read_csv("data/bulk_expression_complete.csv")
  10. pseudo_expr <- read_csv("data/pseudo_bulk_expression.csv")
  11. # 2. Processing Bulk Data
  12. # Calculate mean for the experimental group (py_InR2)
  13. bulk_expr <- bulk_expr %>%
  14. mutate(Exp_mean = rowMeans(select(., py_InR2_1, py_InR2_2, py_InR2_3)))
  15. # 3. Processing Pseudo-bulk Data
  16. common_genes <- intersect(bulk_expr$GeneID, pseudo_expr$GeneID)
  17. bulk_common <- bulk_expr %>% filter(GeneID %in% common_genes)
  18. pseudo_common <- pseudo_expr %>% filter(GeneID %in% common_genes)
  19. pseudo_common_numeric <- pseudo_common %>% select(where(is.numeric))
  20. pseudo_common$Pseudo_mean <- rowMeans(pseudo_common_numeric)
  21. # 4. Merge and Log2 Transformation
  22. plot_data <- merge(bulk_common[, c("GeneID", "Exp_mean")],
  23. pseudo_common[, c("GeneID", "Pseudo_mean")], by = "GeneID") %>%
  24. mutate(log_Bulk = log2(Exp_mean + 1),
  25. log_Pseudo = log2(Pseudo_mean + 1))
  26. # 5. Pearson Correlation and Plotting
  27. r_val <- round(cor(plot_data$log_Pseudo, plot_data$log_Bulk, method = "pearson"), 2)
  28. p <- ggplot(plot_data, aes(x = log_Pseudo, y = log_Bulk)) +
  29. geom_point(alpha = 0.4, size = 1.5, color = "purple") +
  30. geom_smooth(method = "lm", color = "red", se = FALSE) +
  31. labs(x = "log2(Pseudo-bulk Expression + 1)",
  32. y = "log2(Bulk Expression + 1)",
  33. title = paste0("Bulk vs Pseudo-bulk Correlation (r = ", r_val, ")")) +
  34. theme_minimal()
  35. ggsave("results/Bulk_PseudoBulk_Correlation.pdf", p, width = 6, height = 5)

02_Bulk_vs_PseudoBulk_Correlation.R at commit b9dc564, under MIT · at the source

Overview

Authors: Yi Wan1, Hui-Jie Wu1, Heng-Guang Huang1, Zhuo-Qi Liu1, Zhao-Xiang Sun2, Zhang-Nv Yang3, Hai-Jun Xu1
  1. State Key Laboratory of Rice Biology and Breeding, Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Insect Sciences, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
  2. College of Animal Sciences, Zhejiang University, Hangzhou, China
  3. Key Laboratory of Vaccine, Prevention and Control of Infectious Diseases of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
Journal: Nature communications, volume 17, issue 1, article 8236
Dates: received 28 September 2025; accepted 26 June 2026; published online 2 July 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41467-026-75225-z · PMID 42393067 · PMCID PMC13462553 · OpenAlex W7167075247
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: other (organism)
Methods: Statistics, Smoothing, state filtering, decompositions, Evoked potentials, Connectivity
Keywords: Evolutionary developmental biology, Entomology, Morphogenesis
MeSH: Hemiptera*, Wings, Animal*, Animals, Cell Proliferation, Gene Expression Regulation, Developmental, Insect Proteins, RNA Interference, Single-Cell Analysis, Single-Cell Gene Expression Analysis (* major topic)
Topic: Developmental Biology and Gene Regulation (Molecular Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: National Natural Science Foundation of China (32472541, 32272519)
Citations: cited by 2 papers (Europe PMC); 81 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repositories

Its files are read in the Code ↔ Paper reader above, with 6 matches between paragraphs and lines of code.

wanyizju/Pyap-wing-singlecell-2026

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: b9dc564a9fc677a80ff35a20d329b0a78198b026, 18 March 2026
Languages: R (4)
Size: 12 files, 4 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (4 files), pheatmap (2 files), circlize (1 file), ComplexHeatmap (1 file), data.table (1 file), ggplot2 (1 file), Harmony (1 file), Seurat (1 file), SingleCellExperiment (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
6 files

Zenodo 19603850

License: MIT
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (4 files), pheatmap (2 files), circlize (1 file), ComplexHeatmap (1 file), data.table (1 file), ggplot2 (1 file), Harmony (1 file), Seurat (1 file), SingleCellExperiment (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
6 files
At the source:

Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41467-026-75225-z.

Tracing map

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  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 8 scripts, each with its path and the digest of its content;
  • 6 matches between paragraphs of the paper and lines of the code (method lexical-v1);
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Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41467-026-75225-z.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 3 keywords, 9 MeSH terms, 1 funder, 77 references.

Cite

This paper

Wan, Y., Wu, H.-J., Huang, H.-G., Liu, Z.-Q., Sun, Z.-X., Yang, Z.-N., & Xu, H.-J. (2026). A single-cell atlas of alternative wing development in two hemipteran species. Nature communications, 17(1), 8236. https://doi.org/10.1038/s41467-026-75225-z

BibTeX

@article{wan2026single,
author = {Wan, Yi and Wu, Hui-Jie and Huang, Heng-Guang and Liu, Zhuo-Qi and Sun, Zhao-Xiang and Yang, Zhang-Nv and Xu, Hai-Jun},
title = {{A single-cell atlas of alternative wing development in two hemipteran species}},
journal = {Nature communications},
year = {2026},
month = jul,
volume = {17},
number = {1},
pages = {8236},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-75225-z},
url = {https://doi.org/10.1038/s41467-026-75225-z},
pmid = {42393067},
pmcid = {PMC13462553}
}

RIS

TY - JOUR
AU - Wan, Yi
AU - Wu, Hui-Jie
AU - Huang, Heng-Guang
AU - Liu, Zhuo-Qi
AU - Sun, Zhao-Xiang
AU - Yang, Zhang-Nv
AU - Xu, Hai-Jun
TI - A single-cell atlas of alternative wing development in two hemipteran species
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/07/02
VL - 17
IS - 1
SP - 8236
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-75225-z
UR - https://doi.org/10.1038/s41467-026-75225-z
LA - en
ER -

CSL-JSON

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"type": "article-journal",
"title": "A single-cell atlas of alternative wing development in two hemipteran species",
"container-title": "Nature communications",
"author": [
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"family": "Wan",
"given": "Yi"
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"PMCID": "PMC13462553",
"ISSN": "2041-1723",
"publisher": "Nature Publishing Group",
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"language": "en",
"issued": {
"date-parts": [
[
2026,
7,
2
]
]
}
}

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

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