OSCR

Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain.

Code ↔ Paper

40 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 40 matches · 15 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › snRNA-seq data processing and analysis › snRNA-seq feature selection and dimensionality reduction ↔ code/06_preprocessing/02_dimension_reduction.R, lines 1–49 · score 0.94 · nullResiduals, runPCA, Pearson residuals, dimensionality reduction, Poisson deviance, GLM PCA
  2. [2] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Cross-region comparisons › Pseudobulked gene-level dACC and dlPFC comparison ↔ code/11_differential_expression/dream_script_consistent_logFC.R, lines 42–96 · score 0.94 · DGEList, voomWithDreamWeights, calcNormFactors, eBayes, Layer_Tissue, combined gene expression
  3. [3] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Cross-region comparisons › Pseudobulked gene-level dACC and dlPFC comparison ↔ code/11_differential_expression/dream_script.R, lines 44–103 · score 0.91 · DGEList, voomWithDreamWeights, calcNormFactors, eBayes, Layer_Tissue, limma
  4. [4] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Unsupervised clustering of spatial transcriptomics data ↔ code/08_clustering/batch_effect/run_PRECAST_nnSVG_samples_removed.R, the whole file · a weak match · score 0.85 · AddAdjList, AddParSetting, CreatePRECASTObject, CreateSeuratObject, V12N28, clusters
  5. [5] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Unsupervised clustering of spatial transcriptomics data ↔ code/08_clustering/batch_effect/run_PRECAST_nnSVG_samples_and_genes_removed.R, the whole file · a weak match · score 0.85 · AddAdjList, AddParSetting, CreatePRECASTObject, CreateSeuratObject, V12N28, clusters
  6. [6] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Cross-region comparisons › Pseudobulked sample-level dACC and dlPFC comparison ↔ code/12_spatial_registration/DLPFC_manual_spatial_registration.R, the whole file · a weak match · score 0.82 · layer_stat_cor_plot, top_n, registration_wrapper, spatialLIBD, heatmap, DE
  7. [7] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Pseudobulking ↔ code/11_differential_expression/nnSVG_precast_pseudobulk.R, lines 90–156 · score 0.81 · getVarianceExplained, plotExplanatoryVariables, plotPCA, PC2, pseudobulked, spots
  8. [8] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Cross-region comparisons › Pseudobulked sample-level dACC and dlPFC comparison ↔ code/12_spatial_registration/azimuth_spatial_registration.R, the whole file · a weak match · score 0.78 · layer_stat_cor_plot, top_n, registration_wrapper, heatmap, DE, enrichment
  9. [9] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Spatial domain annotation ↔ code/12_spatial_registration/DLPFC_manual_spatial_registration.R, the whole file · a weak match · score 0.77 · layer_stat_cor_plot, top_n, spatialLIBD, confidence, heatmap, enrichment
  10. [10] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › snRNA-seq data processing and analysis › snRNA-seq clustering and cell type annotation ↔ code/07_batch_correction/01_harmony.R, the whole file · a weak match · score 0.77 · RunHarmony, GLM PCA, batch corrected, UMAP, dimensions
  11. [11] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › SRT data processing and analysis › Visium data quality control ↔ code/05_QC/02_qc_metrics.R, lines 1–62 · score 0.75 · low quality spots, addPerCellQC, isOutlier, scuttle, metrics
  12. [12] § RESULTS › NMF reveals cell type-specific gene expression patterns shared between snRNA-seq and SRT data in the dACC ↔ code/13_NMF/DE_NMF38_NMF61.R, lines 146–209 · score 0.74 · MicroPVM, l6 ct, UMAP, Endo, Sncg, VLMC
  13. [13] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Pseudobulked differential expression analysis ↔ code/11_differential_expression/nnSVG_precast_DE.R, lines 244–329 · score 0.74 · EnhancedVolcano, sig_genes_extract, create volcano, cutoff, log10, wrapped
  14. [14] § RESULTS › NMF reveals cell type-specific gene expression patterns shared between snRNA-seq and SRT data in the dACC ↔ code/13_NMF/annotate_NMF_factors.R, lines 1–60 · score 0.73 · microPVM, l6 ct, single nucleus, Endo, Sncg, VLMC
  15. [15] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Spatial domain annotation ↔ code/12_spatial_registration/azimuth_spatial_registration.R, the whole file · a weak match · score 0.72 · layer_stat_cor_plot, top_n, confidence, heatmap, enrichment, model
  16. [16] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › snRNA-seq data processing and analysis › Pseudobulked DE analysis ↔ code/11_differential_expression/nnSVG_precast_DE.R, lines 244–329 · score 0.71 · EnhancedVolcano, sig_genes_extract, create volcano, cutoff, log10, log2
  17. [17] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › snRNA-seq data processing and analysis › snRNA-seq data processing and quality control ↔ code/05_QC/02_qc_metrics.R, lines 1–62 · score 0.70 · addPerCellQC, isOutlier, low quality, scuttle, metrics
  18. [18] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Dorsolateral prefrontal cortex (dlPFC) data › Dorsolateral prefrontal cortex (dlPFC) SRT dataset ↔ code/15_cross_region_snRNA-seq/top_genes_factor.R, lines 25–106 · score 0.70 · spatialDLPFC_Visium, BayesSpace_harmony_09, cross region, meninges, fetch, WM
  19. [19] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Cross-region comparisons › RNAScope quantification - experiment 2 ↔ code/16_VENs_analysis/HALO_L5_GMM.R, lines 1–49 · score 0.67 · cell area, POU3F1, HALO, copy, Br8325, SULF2
  20. [20] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Evaluation of unsupervised clustering of spatial transcriptomics data ↔ code/08_clustering/purity_diagnostics.R, lines 167–213 · score 0.66 · cluster purity, guided PRECAST, nnSVG, discordance
  21. [21] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › SRT data processing and analysis › Visium raw data processing ↔ code/01_spaceranger/spaceranger_2023-03-14_SPag021323.sh, the whole file · a weak match · score 0.66 · VistoSeg, SpaceRanger, alignment, Loupe, FASTQ, Genomics
  22. [22] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › SRT data processing and analysis › Visium raw data processing ↔ code/01_spaceranger/spaceranger_2023-04-03_SPag022423.sh, the whole file · a weak match · score 0.66 · VistoSeg, SpaceRanger, alignment, Loupe, FASTQ, Genomics
  23. [23] § RESULTS › Identification of unique spatio-molecular features in the human dACC ↔ code/11_differential_expression/novel_markers_dACC_DLPFC.R, lines 545–586 · score 0.64 · dlPFC L4, logFC, POU3F1, HAPLN4, PVALB, RORB
  24. [24] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Feature selection, spatially variable genes ↔ code/08_clustering/batch_effect/nnSVG_samples_removed.R, lines 42–130 · score 0.63 · highly ranked, logNormCounts, nnSVG, filter, matrix, genes
  25. [25] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Feature selection, spatially variable genes ↔ code/08_clustering/nnSVG.R, lines 45–127 · score 0.62 · highly ranked, logNormCounts, nnSVG, filter, matrix, genes
  26. [26] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Dorsolateral prefrontal cortex (dlPFC) data › Dorsolateral prefrontal cortex (dlPFC) SRT dataset ↔ code/16_VENs_analysis/01_VAT1L_spot_plots.R, lines 61–124 · score 0.62 · spatialDLPFC_Visium, BayesSpace_harmony_09, meninges, fetch, spatial domain, WM
  27. [27] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › snRNA-seq data processing and analysis › snRNA-seq clustering and cell type annotation ↔ code/10_iSee_app/initial.R, the whole file · a weak match · score 0.59 · iSEE, reduced dimensions, app, UMAP, harmony, clustered
  28. [28] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Dorsolateral prefrontal cortex (dlPFC) data › Dorsolateral prefrontal cortex (dlPFC) snRNA-seq dataset ↔ code/15_cross_region_snRNA-seq/04_project_into_DLPFC_old.R, lines 1–43 · score 0.58 · spatialDLPFC_snRNAseq, cross region, fetch, genes
  29. [29] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Dorsolateral prefrontal cortex (dlPFC) data › Dorsolateral prefrontal cortex (dlPFC) snRNA-seq dataset ↔ code/16_VENs_analysis/RORB_violins.R, the whole file · a weak match · score 0.58 · cellType_layer, spatialDLPFC_snRNAseq, fetch, pseudobulked, dACC, genes
  30. [30] § RESULTS › Localization of a VEN signature to a spatially restricted area of deep L5 in dACC ↔ code/13_NMF/DE_NMF38_NMF61.R, lines 146–209 · score 0.56 · VAT1L, POU3F1, FEZF2, snRNA, NMF38, NMF61
  31. [31] § RESULTS › Localization of a VEN signature to a spatially restricted area of deep L5 in dACC ↔ code/11_differential_expression/novel_markers_dACC_DLPFC.R, lines 42–94 · score 0.54 · VAT1L, POU3F1, FEZF2, HAPLN4, dlPFC, SULF2
  32. [32] § RESULTS › NMF reveals cell type-specific gene expression patterns shared between snRNA-seq and SRT data in the dACC ↔ code/07_batch_correction/01_harmony.R, the whole file · a weak match · score 0.54 · GLM PCA, batch correction, Poisson, dimensions, Harmony
  33. [33] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › SRT data processing and analysis › Visium H&E image processing ↔ code/01_spaceranger/spaceranger_2023-03-14_SPag021323.sh, the whole file · a weak match · score 0.54 · VistoSeg, SpaceRanger, Genomics, slide
  34. [34] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › SRT data processing and analysis › Visium H&E image processing ↔ code/01_spaceranger/spaceranger_2023-04-03_SPag022423.sh, the whole file · a weak match · score 0.54 · VistoSeg, SpaceRanger, Genomics, slide
  35. [35] § RESULTS › Identification of unique spatio-molecular features in the human dACC ↔ code/11_differential_expression/limma_script.R, lines 140–229 · score 0.53 · L2 dlPFC, L5 dlPFC, L6 dlPFC, L6a, DE, L6b
  36. [36] § RESULTS › Localization of a VEN signature to a spatially restricted area of deep L5 in dACC ↔ code/08_clustering/vis_final_precast_labels.R, lines 96–154 · score 0.53 · Br8667_mid, V12Y31, dlPFC Visium, sample ID, B1, Fill
  37. [37] § RESULTS › Identification of unique spatio-molecular features in the human dACC ↔ code/08_clustering/vis_final_precast_labels.R, lines 96–154 · score 0.53 · Br8667_mid, V12Y31, dlPFC Visium, sample ID, B1, Fill
  38. [38] § STAR★METHODS › QUANTIFICATION AND STATISTICAL ANALYSIS › Non-negative matrix factorization (NMF) › NMF annotation ↔ code/14_cross_region/DLPFC_layer_correlation.R, the whole file · a weak match · score 0.52 · technical variables, NMF pattern, correlation, heatmap
  39. [39] § RESULTS › Molecular signatures of spatial gene expression identify discrete spatial domains and reveal agranular laminar patterning in the human dACC ↔ code/08_clustering/purity_diagnostics.R, lines 167–213 · score 0.51 · cluster purity, nnSVG, algorithm, PRECAST
  40. [40] § RESULTS › Spatial domain and cell-type mapping and inference of clinical and functional datasets ↔ code/17_LDSC/NMF/dotplot_visualization.R, lines 54–138 · score 0.51 · Alzheimer, intelligence, bipolar, depression, disease, VIP

Paper

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The authors' code

R · 88 lines · 2.9 KB · no license · 2 matches

  1. setwd('/dcs04/lieber/marmaypag/spatialdACC_LIBD4125/spatialdACC/')
  3. library("here")
  4. library("spatialLIBD")
  5. library("SingleCellExperiment")
  6. library("stringr")
  8. # get reference layer enrichment statistics
  9. #k <- as.numeric(Sys.getenv("SLURM_ARRAY_TASK_ID"))
  11. k=9
  12. nnSVG_precast_name <- paste0("nnSVG_PRECAST_captureArea_", k)
  13. load(file = here("processed-data", "11_differential_expression", "pseudobulk",
  14. "nnSVG_precast_DE", paste0(nnSVG_precast_name,".Rdata")))
  16. # load DLPFC manual annotations
  17. spe <- spatialLIBD::fetch_data(type = "spe")
  19. spe$layer_guess_reordered <- unfactor(spe$layer_guess_reordered)
  20. spe$layer_guess_reordered[spe$layer_guess_reordered == "Layer1"] <- "L1"
  21. spe$layer_guess_reordered[spe$layer_guess_reordered == "Layer2"] <- "L2"
  22. spe$layer_guess_reordered[spe$layer_guess_reordered == "Layer3"] <- "L3"
  23. spe$layer_guess_reordered[spe$layer_guess_reordered == "Layer4"] <- "L4"
  24. spe$layer_guess_reordered[spe$layer_guess_reordered == "Layer5"] <- "L5"
  25. spe$layer_guess_reordered[spe$layer_guess_reordered == "Layer6"] <- "L6"
  26. # remove NA
  27. spe <- spe[,!is.na(spe$layer_guess_reordered)]
  29. table(spe$sample_id, spe$layer_guess_reordered)
  31. spe_pseudo <-
  32. registration_pseudobulk(spe,
  33. var_registration = "layer_guess_reordered",
  34. var_sample_id = "sample_id"
  35. )
  37. spe_modeling_results <- registration_wrapper(
  38. spe,
  39. var_registration = "layer_guess_reordered",
  40. var_sample_id = "sample_id",
  41. gene_ensembl = "gene_id",
  42. gene_name = "gene_name"
  43. )
  45. sig_genes <- sig_genes_extract(
  46. n = 30,
  47. modeling_results = spe_modeling_results,
  48. model_type = "enrichment",
  49. sce_layer = spe_pseudo
  50. )
  52. write.csv(sig_genes, file = here::here("processed-data", "11_differential_expression","pseudobulk", "nnSVG_precast_DE",
  53. paste0("DLPFC_12", "_sig_genes_30.csv")), row.names = FALSE)
  56. ## extract t-statics and rename
  57. registration_t_stats <- spe_modeling_results$enrichment[, grep("^t_stat", colnames(spe_modeling_results$enrichment))]
  58. colnames(registration_t_stats) <- gsub("^t_stat_", "", colnames(registration_t_stats))
  60. ## cell types x gene
  61. dim(registration_t_stats)
  63. ## check out table
  64. registration_t_stats[1:5, 1:5]
  66. cor_layer <- layer_stat_cor(
  67. stats = registration_t_stats,
  68. modeling_results = modeling_results,
  69. model_type = "enrichment",
  70. top_n = 100
  71. )
  73. cor_layer
  74. save(cor_layer, file = here("processed-data", "12_spatial_registration",paste0("DLPFC_12_",nnSVG_precast_name,".rds")))
  76. pdf(file = here::here("plots", "12_spatial_registration", "DLPFC_manual",
  77. paste0("DLPFC_12_",nnSVG_precast_name,"_heatmap.pdf")), width = 14, height = 14)
  78. layer_stat_cor_plot(cor_layer, max = max(cor_layer))
  79. title("DLPFC n=12 vs. dACC")
  80. dev.off()
  82. anno <- annotate_registered_clusters(
  83. cor_stats_layer = cor_layer,
  84. confidence_threshold = 0.25,
  85. cutoff_merge_ratio = 0.25
  86. )
  88. anno

DLPFC_manual_spatial_registration.R at commit c55d35c, no license · at the source

Overview

Authors: Kinnary Shah1, Michael S Totty1, Svitlana V Bach2,3, Madeline R Valentine2, Atharv Chandra2, Haya A AlGrain2, Heena R Divecha2,4, Ryan A Miller2, Felix Rene M Siewe2, Sang Ho Kwon2,4,5, Ishbel Del Rosario Alvia2, Anthony D Ramnauth2,4, Madhavi Tippani2, Sanjana Tyagi2, Joel E Kleinman2,3, Leonardo Collado-Torres1,2,6, Shizhong Han2,3,7, Thomas M Hyde2,3,8, Stephanie C Page2,3, Kristen R Maynard2,3,4, Stephanie C Hicks1,6,9,10,11, Keri Martinowich2,3,4,12,13
ORCID iDs: Kinnary Shah, Felix Rene M Siewe, Keri Martinowich
13 affiliations
  1. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
  2. Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
  3. Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
  4. Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
  5. Biochemistry, Cellular, and Molecular Biology Graduate Program, Johns Hopkins School of Medicine, Baltimore, MD, USA
  6. Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
  7. Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
  8. Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
  9. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
  10. Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
  11. Senior author
  12. Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD, USA
  13. Lead contact
Institutions: Johns Hopkins University (United States); Johns Hopkins Medicine (United States); Lieber Institute for Brain Development (United States); Johns Hopkins Hospital (United States)
Journal: Cell reports, volume 45, issue 6, article 117500
Dates: published online 4 June 2026; in print 23 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1016/j.celrep.2026.117500 · PMID 42241279 · PMCID PMC13359017 · OpenAlex W4412961262
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.1101/2025.07.14.664821
Status: code verified
Categories: genetics / omics (modality), histology / microscopy (modality), human (organism), cellular / molecular (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Machine learning, Preprocessing, Connectivity, fMRI & imaging
Keywords: Dorsal Anterior Cingulate Cortex, Postmortem Human Brain, Spatially Resolved Transcriptomics, Single-nucleus Rna-sequencing, Cp: Molecular Biology, Cp: Neuroscience
MeSH: Gyrus Cinguli*, Adult, Female, Humans, Male, Neurons, Spatial Transcriptomics, Transcriptome (* major topic)
Topic: Neuroinflammation and Neurodegeneration Mechanisms (Neurology, Neuroscience), according to OpenAlex
Funding: NIMH NIH HHS (F32 MH135620, F31 MH013006); NIDA NIH HHS (R01 DA053581); Lieber Institute Inc; National Institutes of Health
Citations: cited by 1 paper (Europe PMC); 106 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

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LieberInstitute/spatialdACC

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: c55d35c52006add72ee0530c596f05b6540ef315, 13 August 2026
Languages: MATLAB (3753), R (248), Shell (95), Perl (60), Python (22)
Size: 35,917 files, 4,178 scripts
Software Heritage: not checked
Found in: the text, “Footnotes”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: ggplot2 (63 files), tidyverse (59 files), patchwork (34 files), pheatmap (27 files), SingleCellExperiment (22 files), cowplot (20 files), igraph (18 files), Seurat (12 files), edgeR (10 files), easystats (8 files), reshape2 (8 files), ComplexHeatmap (5 files), NumPy (3 files), pandas (3 files), Scanpy (3 files), Cell Ranger (2 files), circlize (2 files), reticulate (2 files), ggpubr (1 file), Harmony (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
2,000 files
At the source: github.com/LieberInstitute/spatialdACC

Zenodo 15830481

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: the references
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
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At the source:

research.libd.org/globus

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: the link answers
Software Heritage: not checked
Found in: the text, “Footnotes”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
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At the source: research.libd.org/globus/

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Data

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Version 2, 28 September 2026

  • Publisher: n/a → Cell Press
  • Authors: added Keri Martinowich (0000-0002-5237-0789); removed Keri Martinowich

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 22 authors, 6 keywords, 8 MeSH terms, 4 funders, 100 references.

Cite

This paper

Shah, K., Totty, M. S., Bach, S. V., Valentine, M. R., Chandra, A., AlGrain, H. A., Divecha, H. R., Miller, R. A., Siewe, F. R. M., Kwon, S. H., Del Rosario Alvia, I., Ramnauth, A. D., Tippani, M., Tyagi, S., Kleinman, J. E., Collado-Torres, L., Han, S., Hyde, T. M., Page, S. C., . . . Martinowich, K. (2026). Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain. Cell reports, 45(6), 117500. https://doi.org/10.1016/j.celrep.2026.117500

BibTeX

@article{shah2026spatio,
author = {Shah, Kinnary and Totty, Michael S and Bach, Svitlana V and Valentine, Madeline R and Chandra, Atharv and AlGrain, Haya A and Divecha, Heena R and Miller, Ryan A and Siewe, Felix Rene M and Kwon, Sang Ho and Del Rosario Alvia, Ishbel and Ramnauth, Anthony D and Tippani, Madhavi and Tyagi, Sanjana and Kleinman, Joel E and Collado-Torres, Leonardo and Han, Shizhong and Hyde, Thomas M and Page, Stephanie C and Maynard, Kristen R and Hicks, Stephanie C and Martinowich, Keri},
title = {{Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain}},
journal = {Cell reports},
year = {2026},
month = jun,
volume = {45},
number = {6},
pages = {117500},
publisher = {Cell Press},
issn = {2211-1247},
doi = {10.1016/j.celrep.2026.117500},
url = {https://doi.org/10.1016/j.celrep.2026.117500},
pmid = {42241279},
pmcid = {PMC13359017}
}

RIS

TY - JOUR
AU - Shah, Kinnary
AU - Totty, Michael S
AU - Bach, Svitlana V
AU - Valentine, Madeline R
AU - Chandra, Atharv
AU - AlGrain, Haya A
AU - Divecha, Heena R
AU - Miller, Ryan A
AU - Siewe, Felix Rene M
AU - Kwon, Sang Ho
AU - Del Rosario Alvia, Ishbel
AU - Ramnauth, Anthony D
AU - Tippani, Madhavi
AU - Tyagi, Sanjana
AU - Kleinman, Joel E
AU - Collado-Torres, Leonardo
AU - Han, Shizhong
AU - Hyde, Thomas M
AU - Page, Stephanie C
AU - Maynard, Kristen R
AU - Hicks, Stephanie C
AU - Martinowich, Keri
TI - Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain
T2 - Cell reports
J2 - Cell Rep
PY - 2026
DA - 2026/06/04
VL - 45
IS - 6
SP - 117500
SN - 2211-1247
PB - Cell Press
DO - 10.1016/j.celrep.2026.117500
UR - https://doi.org/10.1016/j.celrep.2026.117500
LA - en
ER -

CSL-JSON

{
"id": "10.1016/j.celrep.2026.117500",
"type": "article-journal",
"title": "Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain",
"container-title": "Cell reports",
"author": [
{
"family": "Shah",
"given": "Kinnary"
},
{
"family": "Totty",
"given": "Michael S"
},
{
"family": "Bach",
"given": "Svitlana V"
},
{
"family": "Valentine",
"given": "Madeline R"
},
{
"family": "Chandra",
"given": "Atharv"
},
{
"family": "AlGrain",
"given": "Haya A"
},
{
"family": "Divecha",
"given": "Heena R"
},
{
"family": "Miller",
"given": "Ryan A"
},
{
"family": "Siewe",
"given": "Felix Rene M"
},
{
"family": "Kwon",
"given": "Sang Ho"
},
{
"family": "Del Rosario Alvia",
"given": "Ishbel"
},
{
"family": "Ramnauth",
"given": "Anthony D"
},
{
"family": "Tippani",
"given": "Madhavi"
},
{
"family": "Tyagi",
"given": "Sanjana"
},
{
"family": "Kleinman",
"given": "Joel E"
},
{
"family": "Collado-Torres",
"given": "Leonardo"
},
{
"family": "Han",
"given": "Shizhong"
},
{
"family": "Hyde",
"given": "Thomas M"
},
{
"family": "Page",
"given": "Stephanie C"
},
{
"family": "Maynard",
"given": "Kristen R"
},
{
"family": "Hicks",
"given": "Stephanie C"
},
{
"family": "Martinowich",
"given": "Keri"
}
],
"container-title-short": "Cell Rep",
"volume": "45",
"issue": "6",
"page": "117500",
"DOI": "10.1016/j.celrep.2026.117500",
"PMID": "42241279",
"PMCID": "PMC13359017",
"ISSN": "2211-1247",
"publisher": "Cell Press",
"URL": "https://doi.org/10.1016/j.celrep.2026.117500",
"language": "en",
"issued": {
"date-parts": [
[
2026,
6,
4
]
]
}
}

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