BrainEnrich: Revealing Biological Insights for Imaging-Derived Phenotypes Through Transcriptomic Enrichment.

Code ↔ Paper

4 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 4 matches

[1] § Methods › BrainEnrich Analytical Framework › Association Methods ↔ 2024_NI_Imaging_Transcriptomics/misc/find_odd_brain.R, lines 1–57 · score 0.59 · pls1w, brain map, Pearson, imaging transcriptomics, permutation, weights
[2] § Methods › Simulation Studies › Type 1 Error Simulations ↔ 2024_NI_Imaging_Transcriptomics/functions/vacc_function.R, lines 2–80 · score 0.58 · resampled gene, SynGO, spin, GS, correlation, scores
[3] § Methods › BrainEnrich Analytical Framework › Group‐Level Enrichment Analysis ↔ 2024_NI_Imaging_Transcriptomics/functions/vacc_function.R, lines 2–80 · score 0.58 · aggregate gene, resampling genes, spinning brain, LOO, imaging transcriptomics, GS
[4] § Methods › Simulation Studies › Simulation Data and Setup ↔ 2024_NI_Imaging_Transcriptomics/data/BrainInfo/perm_id_weights/generate_permID_MoranW.R, lines 22–110 · score 0.53 · right hemisphere, left hemisphere, temporal, transformed, matched, transcriptional

Paper

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The authors' code

R · 113 lines · 4.8 KB · no license · 2 matches

vacc_function<-function(
data_path='F:/Google Drive/post-doc/vitural_histology_revisit/revision_code/data',
atlas=c('desikan',
'schaefer100',
'schaefer200'),
rdonor=c('r0.2',
'r0.4',
'r0.6'),
gs_type=c('MF',
'Sim',
'SynGO'),
brain_type=c('sample_data',
'sim_nospatial',
'sim_spatial0.03',
'sim_spatial0.02',
'sim_spatial0.01',
'real_brain'),
null_type=c('spin_brain','random_gene','random_gene_coexp', 'random_gene_subset','spin_random_mixed'),
cor_type=c('pearson','spearman','loo','pls1','pls1w'),
sampled_geneSetList=NULL, # any constrained sampled_geneSetList for random_gene?
slrum_idx=1){
# print all input parameters
cat('==========\n')
cat('input parameters for vacc fun:\n')
cat(sprintf('data_path: %s\n',data_path))
cat(sprintf('atlas: %s\n',atlas))
cat(sprintf('rdonor: %s\n',rdonor))
cat(sprintf('gs_type: %s\n',gs_type))
cat(sprintf('brain_type: %s\n',brain_type))
cat(sprintf('null_type: %s\n',null_type))
cat(sprintf('cor_type: %s\n',cor_type))
cat(sprintf('is null sampled_geneSetList: %s\n',is.null(sampled_geneSetList)))
cat(sprintf('slrum_idx: %s\n',slrum_idx))
cat('==========\n')
brain_data=load_BrainDat(data_path=sprintf('%s/BrainDat',data_path),
atlas=atlas,
type=brain_type,
col_idx=slrum_idx)
gene_data=load_GeneExp(data_path=sprintf('%s/GeneExp',data_path),
atlas=atlas,
rdonor=rdonor)
geneSetList=load_GeneSets(data_path=sprintf('%s/GeneSets',data_path),
atlas=atlas,
rdonor=rdonor,
gs_type=gs_type)
geneList.true=corr_brain_gene(gene_data,brain_data,method=cor_type)
if (null_type=='random_gene') {
geneList.null = resampling_geneList(geneList.true)
} else if (null_type=='spin_brain'){
perm.id = load_permid(data_path=sprintf('%s/BrainInfo/perm_id_weights',data_path),
atlas=atlas,
type='spin_brain')
null_brain_data = generate_null_brain_data(brain_data, perm.id)
geneList.null = corr_brain_gene(gene_data, null_brain_data,method=cor_type)
} else if (null_type=='spin_random_mixed'){
perm.id = load_permid(data_path=sprintf('%s/BrainInfo/perm_id_weights',data_path),
atlas=atlas,
type='spin_brain')
null_brain_data = generate_null_brain_data(brain_data, perm.id)
geneList.tmp = corr_brain_gene(gene_data, null_brain_data,method=cor_type)
geneList.null = apply(geneList.tmp,2,sample)
row.names(geneList.null)=row.names(geneList.tmp)
colnames(geneList.null)=paste0('null_',c(1:5000))
attr(geneList.null,'is_fisherz')=attr(geneList.tmp,'is_fisherz')
attr(geneList.null,'n.region')=attr(geneList.tmp,'n.region')
}
cat('==========\n')
cat('start testing \n')
res=list()
for (method2test in c('mean','median','meanabs','meansqr','maxmean','sig_n','ks_orig','ks_weighted')){
if (cor_type %in% c('pls1','loo','pls1w')& method2test=='sig_n'){ # skip sig_n for pls1 and loo
next
}
cat(paste0(method2test,'....\n'))
score.true=aggregate_geneSetList(geneSetList, geneList.true,method=method2test)
# caculate null stats
if (null_type %in% c('random_gene','spin_brain','spin_random_mixed')){ # resampling without constrains
score.null=aggregate_geneSetList(geneSetList, geneList.null,method=method2test)
} else { # resampling with constrains
if (is.null(sampled_geneSetList)){
stop('sampled_geneSetList is required for random_gene_coexp and random_gene_subset')
}
score.null=aggregate_geneSetList_with_constrain(geneSetList = geneSetList,
sampled_geneSetList = sampled_geneSetList,
geneList = geneList.true,
method=method2test)
}
# caculate p value based on true and null stats
if (method2test %in% c('ks_orig','ks_weighted')){
pvals=caculate_pvals(score.true,score.null,method='split_pos_neg')
} else {
pvals=caculate_pvals(score.true,score.null,method='standard')
}
res[[method2test]][['pvals']]=pvals
rm(score.true,score.null,pvals)
}
# format res to a data.frame
df.list=list()
for (var2extract in c('pvals')){
df.list[[var2extract]]= as.data.frame(lapply(res, function(x){do.call(rbind,x[[var2extract]])}))
}
df2save=do.call(cbind,df.list) %>% tibble::rownames_to_column("geneSet") %>% mutate(sim_brain=slrum_idx)
return(df2save)
}

vacc_function.R at commit 54c690f, no license · at the source

OverviewAuthors: Zhipeng Cao1,2, Dekang Yuan3, Jinmei Qin1, Yujie Wu1, Chenhu Li1, Guilai Zhan1
ORCID iDs: Zhipeng Cao, Dekang Yuan
Shanghai Xuhui Mental Health Center Shanghai China
School of Mental Health Wenzhou Medical University Wenzhou Zhejiang China
Department of Psychiatry University of Vermont College of Medicine Burlington Vermont USA
Institutions: Wenzhou Medical University (China); Shanghai Mental Health Center (China); University of Vermont (United States); University of Vermont Medical Center (United States)
Journal: Human brain mapping, volume 47, issue 10, article e70605
Dates: received 20 March 2026; accepted 6 July 2026; published online 12 July 2026; in print July 2026
Type: Other · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1002/hbm.70605 · PMID 42438110 · PMCID PMC13357997 · OpenAlex W7168154215
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: genetics / omics (modality), human (organism), depression (population)
Methods: Connectivity, Statistics, Machine learning, Smoothing, state filtering, decompositions, Preprocessing
Keywords: Allen Human Brain Atlas, competitive null model, gene set enrichment, imaging transcriptomics, imaging‐derived phenotypes, individual‐level analysis, self‐contained null model
MeSH: Brain*, Gene Expression Profiling*, Major Depressive Disorder*, Neuroimaging*, Transcriptome*, Atlases as Topic, Humans, Phenotype (* major topic)
Journal subjects: Toolbox
Topic: Single-cell and spatial transcriptomics (Molecular Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: National Natural Science Foundation of China (32400925); Key Medical Discipline Program of Shanghai Xuhui District (SHXHZDXK202308); Medical Research Project of Shanghai Xuhui District (SHXH202305, SHXH202504, SHXH202401)
Citations: not cited yet (Europe PMC); 76 references in the paper
AbstractThe 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 4 matches between paragraphs and lines of code.

YuLab-SMU/enrichplot

License: none: the authors keep all their rights

State: the link answers, verified on 27 September 2026

Evidence: files inventoried

Commit: 572e6add5507616d9ebd2267669e4a754691e3fa, 27 September 2026

Languages: R (54)

Size: 115 files, 54 scripts

Software Heritage: not archived

Found in: “Data and Code Availability”

Holds: README, environment (DESCRIPTION), tests, documentation, 2 notebooks

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

Tools: ggplot2 (27 files), tidyverse (9 files), igraph (7 files), reshape2 (2 files), clusterProfiler (1 file), cowplot (1 file)

Availability: 1 check, the latest on 27 September 2026: the link answers

27 September 2026: the link answers

55 files

R/00-AllClasses.R, R, 3 lines
R/00-utils.R, R, 57 lines
R/AllGenerics.R, R, 669 lines
R/barplot.R, R, 205 lines
R/cnetplot.R, R, 900 lines
R/color_utils.R, R, 158 lines
R/consensusmap.R, R, 196 lines
R/converters.R, R, 336 lines
R/data_utils.R, R, 397 lines
R/densityplot.R, R, 51 lines
R/dotplot.R, R, 895 lines
R/emapplot.R, R, 721 lines
R/emapplot_utilities.R, R, 596 lines
R/enrichplot-package.R, R, 3 lines
R/external-results.R, R, 45 lines
R/ggtable.R, R, 47 lines
R/goplot.R, R, 120 lines
R/gseaplot.R, R, 881 lines
R/heatplot.R, R, 409 lines
R/manhattanplot.R, R, 431 lines
R/mechanismflow.R, R, 165 lines
R/method-fortify.R, R, 384 lines
R/method-ggplot-add.R, R, 26 lines
R/method-print.r, R, 7 lines
R/mnsea-helpers.R, R, 309 lines
R/nsea-mechanism-helpers.R, R, 398 lines
R/pairwise_termsim.R, R, 129 lines
R/phaseplot.R, R, 132 lines
R/plot_utils.R, R, 149 lines
R/pmcplot.R, R, 59 lines
R/reexport.R, R, 46 lines
R/rewireplot.R, R, 158 lines
R/ridgeplot.R, R, 406 lines
R/ssplot.R, R, 585 lines
R/treeplot.R, R, 694 lines
R/upsetplot.R, R, 259 lines
R/volplot.R, R, 50 lines
R/wordcloud.R, R, 121 lines
R/zzz.R, R, 7 lines
README.Rmd, R, 80 lines
tests/testthat.R, R, 4 lines
tests/testthat/helper-mock-results.R, R, 254 lines
tests/testthat/test-consensusmap.R, R, 80 lines
tests/testthat/test-converters.R, R, 198 lines
tests/testthat/test-edge-filtering.R, R, 127 lines
tests/testthat/test-mechanismflow.R, R, 66 lines
tests/testthat/test-mnsea-helpers.R, R, 613 lines
tests/testthat/test-nsea-mechanism-helpers.R, R, 126 lines
tests/testthat/test-nsea-support.R, R, 60 lines
tests/testthat/test-phaseplot.R, R, 82 lines
tests/testthat/test-plotting-regression.R, R, 754 lines
tests/testthat/test-rewireplot.R, R, 53 lines
tests/testthat/test-stability-fixes.R, R, 368 lines
vignettes/enrichplot.Rmd, R, 30 lines
README.md, Text, 62 lines

At the source: github.com/YuLab-SMU/enrichplot

zh1peng/paper_code

License: none: the authors keep all their rights

State: the link answers, verified on 27 September 2026

Evidence: files inventoried

Commit: 54c690f8c151c83a7bdf5ade73fa22de3c99dccf, 7 March 2025

Languages: R (131), MATLAB (62), Python (16), Shell (1), C++ (1)

Size: 595 files, 211 scripts

Software Heritage: archived

Found in: “Data and Code Availability”

Holds: README, 22 notebooks

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

Tools: tidyverse (56 files), ggplot2 (23 files), SPM (20 files), lmerTest (18 files), pandas (13 files), NiBabel (12 files), ggseg (7 files), Statistics and Machine Learning Toolbox (7 files), nlme (7 files), NumPy (7 files), EEGLAB (6 files), SciPy (5 files), JAGS (4 files), netneurotools (4 files), patchwork (4 files), broom (2 files), easystats (2 files), emmeans (2 files), fdr_bh (Benjamini-Hochberg FDR) (2 files), clusterProfiler (1 file), FreeSurfer (1 file), ggpubr (1 file), Matplotlib (1 file), pheatmap (1 file), reticulate (1 file), scikit-learn (1 file)

Availability: 1 check, the latest on 27 September 2026: the link answers

27 September 2026: the link answers

212 files

2020_ADB_RPE_Drinkers/1_RPE_modelling&RT/RT_eMID.m, MATLAB, 82 lines
2020_ADB_RPE_Drinkers/1_RPE_modelling&RT/RW_eMID.m, MATLAB, 142 lines
2020_ADB_RPE_Drinkers/1_RPE_modelling&RT/extract_eMID_info.m, MATLAB, 35 lines
2020_ADB_RPE_Drinkers/2_Extract_epochs/extract_PE_ERPs.m, MATLAB, 61 lines
2020_ADB_RPE_Drinkers/3_Single_trial_analysis/PE_single_trial_analysis.m, MATLAB, 319 lines
2020_ADB_RPE_Drinkers/4_Averaged_ERP_analysis/Avearged_ERP_analysis.m, MATLAB, 470 lines
2020_ADB_RPE_Drinkers/5_SI&MISC/FigureS1.m, MATLAB, 78 lines
2020_ADB_RPE_Drinkers/5_SI&MISC/consecutive_number.m, MATLAB, 14 lines
2020_ADB_RPE_Drinkers/5_SI&MISC/erp2spss.m, MATLAB, 68 lines
2020_ADB_RPE_Drinkers/5_SI&MISC/fdr_bh.m, MATLAB, 226 lines
2020_ADB_RPE_Drinkers/5_SI&MISC/report RPE modulation permutation effects.m, MATLAB, 37 lines
2020_ADB_RPE_Drinkers/5_SI&MISC/struct2vector.m, MATLAB, 12 lines
2021_ADB_Brain_Asymmetry/0_run_all_analysis.R, R, 66 lines
2021_ADB_Brain_Asymmetry/10_residulize_aidata.R, R, 14 lines
2021_ADB_Brain_Asymmetry/10_residulize_aidata_normalize.R, R, 14 lines
2021_ADB_Brain_Asymmetry/11_residulize_LRdata.R, R, 14 lines
2021_ADB_Brain_Asymmetry/12_residulized_plots.R, R, 80 lines
2021_ADB_Brain_Asymmetry/13_ML_load_data.R, R, 91 lines
2021_ADB_Brain_Asymmetry/14_past_30_day_alc_analysis.R, R, 82 lines
2021_ADB_Brain_Asymmetry/15_past_30_day_nic_analysis.R, R, 81 lines
2021_ADB_Brain_Asymmetry/1_load_data.R, R, 79 lines
2021_ADB_Brain_Asymmetry/2_model1_analysisl.R, R, 121 lines
2021_ADB_Brain_Asymmetry/3_model1_bar_plot.R, R, 86 lines
2021_ADB_Brain_Asymmetry/4_model1_cohend_map.R, R, 55 lines
2021_ADB_Brain_Asymmetry/5_model2_analysis.R, R, 123 lines
2021_ADB_Brain_Asymmetry/6_model2_cohend_map.R, R, 53 lines
2021_ADB_Brain_Asymmetry/7_model2_mcc_across_substance.R, R, 24 lines
2021_ADB_Brain_Asymmetry/8_model2_post_hoc_analysis.R, R, 18 lines
2021_ADB_Brain_Asymmetry/9_model2_bar_plot.R, R, 101 lines
2021_ADB_Brain_Asymmetry/svm_classification_code.py, Python, 95 lines
2021_DCN_MID_Development/10_Behavioural_performance_T1_vs_T2/RT_LME_analysis.R, R, 206 lines
2021_DCN_MID_Development/11_Brain_response_T1_vs_T2_alcohol_interaction/intersection_LME_null_model.R, R, 52 lines
2021_DCN_MID_Development/11_Brain_response_T1_vs_T2_alcohol_interaction/intersection_LME_true_model.R, R, 42 lines
2021_DCN_MID_Development/11_Brain_response_T1_vs_T2_alcohol_interaction/merge_con_files/merge_con_files_by_subid.py, Python, 24 lines
2021_DCN_MID_Development/11_Brain_response_T1_vs_T2_alcohol_interaction/tfce_t_maps_vacc_extract_perm.m, MATLAB, 110 lines
2021_DCN_MID_Development/11_Brain_response_T1_vs_T2_alcohol_interaction/tfce_t_maps_vacc_raw.m, MATLAB, 44 lines
2021_DCN_MID_Development/11_Brain_response_T1_vs_T2_alcohol_interaction/vx_LME_functions_interaction.R, R, 285 lines
2021_DCN_MID_Development/12_VS_Functional_Connectivity_T1_vs_T2_alcohol_interaction/PPI_L_VS/intersection_LME_null_model.R, R, 52 lines
2021_DCN_MID_Development/12_VS_Functional_Connectivity_T1_vs_T2_alcohol_interaction/PPI_L_VS/intersection_LME_true_model.R, R, 42 lines
2021_DCN_MID_Development/12_VS_Functional_Connectivity_T1_vs_T2_alcohol_interaction/PPI_R_VS/intersection_LME_null_model.R, R, 52 lines
2021_DCN_MID_Development/12_VS_Functional_Connectivity_T1_vs_T2_alcohol_interaction/PPI_R_VS/intersection_LME_true_model.R, R, 42 lines
2021_DCN_MID_Development/12_VS_Functional_Connectivity_T1_vs_T2_alcohol_interaction/merge_con_files/bsl_merge_con_files_by_subid.py, Python, 16 lines
2021_DCN_MID_Development/12_VS_Functional_Connectivity_T1_vs_T2_alcohol_interaction/merge_con_files/fu2_merge_con_files_by_subid.py, Python, 16 lines
2021_DCN_MID_Development/12_VS_Functional_Connectivity_T1_vs_T2_alcohol_interaction/vx_LME_functions_interaction.R, R, 285 lines
2021_DCN_MID_Development/13_Graph_metric_T1_vs_T2_alchol_interaction/alc_test_add_posthoc.R, R, 191 lines
2021_DCN_MID_Development/13_Graph_metric_T1_vs_T2_alchol_interaction/alc_test_with_permutation.R, R, 210 lines
2021_DCN_MID_Development/13_Graph_metric_T1_vs_T2_alchol_interaction/merge_all_data.R, R, 105 lines
2021_DCN_MID_Development/14_SI&Revision/1_Brain_response_T1_T2_add_effect_size/LME_true_model.R, R, 40 lines
2021_DCN_MID_Development/14_SI&Revision/1_Brain_response_T1_T2_add_effect_size/vx_LME_functions_time_sex_es.R, R, 355 lines
2021_DCN_MID_Development/14_SI&Revision/2_drop_out_variance_test/find_drop_out_participants_test_var.R, R, 115 lines
2021_DCN_MID_Development/14_SI&Revision/2_drop_out_variance_test/g1_merge_cons/merge_con_files_by_subid.py, Python, 25 lines
2021_DCN_MID_Development/14_SI&Revision/2_drop_out_variance_test/g2_merge_cons/merge_con_files_by_subid.py, Python, 25 lines
2021_DCN_MID_Development/14_SI&Revision/2_drop_out_variance_test/vx_test_on_variance.R, R, 113 lines
2021_DCN_MID_Development/14_SI&Revision/3_test_different_AUDIT/alc_changes.R, R, 170 lines
2021_DCN_MID_Development/14_SI&Revision/3_test_different_AUDIT/alc_cutoff_25perc_analysis.R, R, 191 lines
2021_DCN_MID_Development/14_SI&Revision/3_test_different_AUDIT/alc_cutoff_l2h7_analysis.R, R, 185 lines
2021_DCN_MID_Development/14_SI&Revision/3_test_different_AUDIT/alc_cutoff_l3h8_analysis.R, R, 192 lines
2021_DCN_MID_Development/14_SI&Revision/3_test_different_AUDIT/alc_l3hx_test_code.R, R, 223 lines
2021_DCN_MID_Development/14_SI&Revision/SI_prob_maps/create_prob_map_function.m, MATLAB, 254 lines
2021_DCN_MID_Development/14_SI&Revision/SI_prob_maps/make_2nd_level_jobfile.m, MATLAB, 18 lines
2021_DCN_MID_Development/14_SI&Revision/SI_prob_maps/prob_map_report.m, MATLAB, 56 lines
2021_DCN_MID_Development/14_SI&Revision/SI_prob_maps/run_prob_maps_job.m, MATLAB, 10 lines
2021_DCN_MID_Development/14_SI&Revision/SI_prob_maps/select_group.m, MATLAB, 36 lines
2021_DCN_MID_Development/15_other/1_report_participants/alc_report.R, R, 114 lines
2021_DCN_MID_Development/15_other/1_report_participants/report_all_code.R, R, 84 lines
2021_DCN_MID_Development/15_other/2_test_node_coverage/BSL_sphere_test.m, MATLAB, 8 lines
2021_DCN_MID_Development/15_other/2_test_node_coverage/FU2_sphere_test.m, MATLAB, 8 lines
2021_DCN_MID_Development/15_other/2_test_node_coverage/sphere_testing.m, MATLAB, 61 lines
2021_DCN_MID_Development/15_other/3_longitudinal_plot/longitudinal_plot.R, R, 325 lines
2021_DCN_MID_Development/1_prepare_MRI_data/BSL_4D_split_copy.py, Python, 49 lines
2021_DCN_MID_Development/1_prepare_MRI_data/FU2_4D_split_copy.py, Python, 50 lines
2021_DCN_MID_Development/1_prepare_MRI_data/bsl_manually_split_copy.m, MATLAB, 36 lines
2021_DCN_MID_Development/1_prepare_MRI_data/fu2_manually_split_copy.m, MATLAB, 36 lines
2021_DCN_MID_Development/2_Brain_response_1st_level/bsl_1st_level_vacc_function.m, MATLAB, 150 lines
2021_DCN_MID_Development/2_Brain_response_1st_level/fu2_1st_level_vacc_function.m, MATLAB, 147 lines
2021_DCN_MID_Development/3_VS_Functional_Connectivity_individual_level/bsl_PPI_1st_level_vacc_function.m, MATLAB, 115 lines
2021_DCN_MID_Development/3_VS_Functional_Connectivity_individual_level/fu2_PPI_1st_level_vacc_function.m, MATLAB, 104 lines
2021_DCN_MID_Development/3_VS_Functional_Connectivity_individual_level/my_spm_peb_ppi.m, MATLAB, 417 lines
2021_DCN_MID_Development/3_VS_Functional_Connectivity_individual_level/my_spm_regions.m, MATLAB, 302 lines
2021_DCN_MID_Development/4_Task_modulated_network_individual_level/bsl_fc_map_vacc_function.m, MATLAB, 19 lines
2021_DCN_MID_Development/4_Task_modulated_network_individual_level/fu2_fc_map_vacc_function.m, MATLAB, 19 lines
2021_DCN_MID_Development/4_Task_modulated_network_individual_level/mid_fc_map.m, MATLAB, 49 lines
2021_DCN_MID_Development/4_Task_modulated_network_individual_level/my_spm_regions.m, MATLAB, 301 lines
2021_DCN_MID_Development/4_Task_modulated_network_individual_level/simple_PPI.m, MATLAB, 488 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/bsl_calculate_network_vacc_function.m, MATLAB, 27 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/export_net_node_gt2LME.m, MATLAB, 23 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/fu2_calculate_network_vacc_function.m, MATLAB, 27 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/net_results_extraction.m, MATLAB, 122 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/network_resutls_extraction.m, MATLAB, 12 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/node_results_extraction.m, MATLAB, 119 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/run_extraction.m, MATLAB, 11 lines
2021_DCN_MID_Development/5_Graph_metrics_individual_level/subid_test.m, MATLAB, 5 lines
2021_DCN_MID_Development/6_Behavioural_QC/BSL_parse_csvinfo_after_QC.m, MATLAB, 178 lines
2021_DCN_MID_Development/6_Behavioural_QC/BSL_parse_csvinfo_before_QC.m, MATLAB, 178 lines
2021_DCN_MID_Development/6_Behavioural_QC/FU2_parse_csvinfo_after_QC.m, MATLAB, 206 lines
2021_DCN_MID_Development/6_Behavioural_QC/FU2_parse_csvinfo_before_QC.m, MATLAB, 206 lines
2021_DCN_MID_Development/6_Behavioural_QC/bsl_find_good_subid.m, MATLAB, 20 lines
2021_DCN_MID_Development/6_Behavioural_QC/fu2_find_good_subid.m, MATLAB, 20 lines
2021_DCN_MID_Development/7_Brain_response_T1_vs_T2/LME_null_model.R, R, 50 lines
2021_DCN_MID_Development/7_Brain_response_T1_vs_T2/LME_true_model.R, R, 42 lines
2021_DCN_MID_Development/7_Brain_response_T1_vs_T2/tfce_t_maps_vacc_extract_perm.m, MATLAB, 46 lines
2021_DCN_MID_Development/7_Brain_response_T1_vs_T2/tfce_t_maps_vacc_raw.m, MATLAB, 44 lines
2021_DCN_MID_Development/7_Brain_response_T1_vs_T2/vx_LME_functions_time_sex.R, R, 316 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_L_VS/LME_null_model.R, R, 50 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_L_VS/LME_true_model.R, R, 42 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_L_VS/tfce_t_maps_vacc_extract_perm.m, MATLAB, 116 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_L_VS/tfce_t_maps_vacc_raw.m, MATLAB, 44 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_R_VS/LME_null_model.R, R, 50 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_R_VS/LME_true_model.R, R, 42 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_R_VS/tfce_t_maps_vacc_extract_perm.m, MATLAB, 116 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/PPI_R_VS/tfce_t_maps_vacc_raw.m, MATLAB, 44 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/bsl_merge_con_files_by_subid.py, Python, 16 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/fu2_merge_con_files_by_subid.py, Python, 16 lines
2021_DCN_MID_Development/8_VS_Functional_Connectivity_T1_vs_T2/vx_LME_functions_time_sex.R, R, 316 lines
2021_DCN_MID_Development/9_Graph_metrics_T1_vs_T2/WU_net_node_gt_LME_analysis.R, R, 162 lines
2021_DCN_MID_Development/9_Graph_metrics_T1_vs_T2/WU_net_results_plot.R, R, 151 lines
2023_FIN_Bayesian_adjustment/0_analysis_functions.R, R, 77 lines
2023_FIN_Bayesian_adjustment/0_combat_for_ENIGMA_sMRI.R, R, 380 lines
2023_FIN_Bayesian_adjustment/0_load_data.R, R, 96 lines
2023_FIN_Bayesian_adjustment/1_prepare_combat_data.R, R, 83 lines
2023_FIN_Bayesian_adjustment/2_one_site_es_sampling_vacc_function.R, R, 35 lines
2023_FIN_Bayesian_adjustment/3_Hierachical_Bayesian_model.R, R, 158 lines
2023_FIN_Bayesian_adjustment/4_brain_plot_and_ridge_plot_for_overarching_estimates.R, R, 147 lines
2023_FIN_Bayesian_adjustment/5_report_overarching_estimates.R, R, 83 lines
2023_FIN_Bayesian_adjustment/6_ridge_plot_for_each_study.R, R, 262 lines
2023_FIN_Bayesian_adjustment/revision/revision_code_ComBat_and_normality.R, R, 146 lines
2023_FIN_Bayesian_adjustment/revision/revision_code_plot_gamma.R, R, 47 lines
2023_FIN_Bayesian_adjustment/revision/revision_code_test_MCMC_no_ComBat.R, R, 154 lines
2023_FIN_Bayesian_adjustment/revision/revision_code_test_different_gama_narrower.R, R, 154 lines
2023_FIN_Bayesian_adjustment/revision/revision_code_test_different_gama_wider.R, R, 154 lines
2023_FIN_Bayesian_adjustment/revision/revision_make_brain_ridge_plot.R, R, 113 lines
2023_FIN_Bayesian_adjustment/revision/revision_make_regional_plots.R, R, 147 lines
2023_FIN_Bayesian_adjustment/revision/revision_make_tables.R, R, 100 lines
2023_MP_Cross_disorder_Neurodevelopment/RSI_analysis/RSI_vacc_permutation.R, R, 46 lines
2023_MP_Cross_disorder_Neurodevelopment/RSI_analysis/prepare_rsi_measures.R, R, 86 lines
2023_MP_Cross_disorder_Neurodevelopment/analysis_script.R, R, 698 lines
2023_MP_Cross_disorder_Neurodevelopment/correlation_functions.R, R, 116 lines
2023_MP_Cross_disorder_Neurodevelopment/external_functions.R, R, 462 lines
2023_MP_Cross_disorder_Neurodevelopment/group_comp_functions.R, R, 343 lines
2023_MP_Cross_disorder_Neurodevelopment/gsea_functions.R, R, 378 lines
2023_MP_Cross_disorder_Neurodevelopment/pSI_data/making_pSI_tables.R, R, 24 lines
2023_MP_Cross_disorder_Neurodevelopment/pca_functions.R, R, 371 lines
2023_MP_Cross_disorder_Neurodevelopment/vertex_PCA/how2use_process_vertex_pca_results.m, MATLAB, 6 lines
2023_MP_Cross_disorder_Neurodevelopment/vertex_PCA/merge_mgh_by_subid2merge.py, Python, 71 lines
2023_MP_Cross_disorder_Neurodevelopment/vertex_PCA/pca_vertex_cmd.R, R, 138 lines
2023_MP_Cross_disorder_Neurodevelopment/vertex_PCA/process_vertex_pca_results.m, MATLAB, 44 lines
2023_MP_Cross_disorder_Neurodevelopment/vertex_PCA/test_exist_file.py, Python, 18 lines
2024_NI_Imaging_Transcriptomics/analysis/Main.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S1-Moran0.02.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S10-PLS1.Rmd, R, 345 lines
2024_NI_Imaging_Transcriptomics/analysis/S11-PLS1-Coexp_matched.Rmd, R, 186 lines
2024_NI_Imaging_Transcriptomics/analysis/S12-PLS1-Brain_specific.Rmd, R, 186 lines
2024_NI_Imaging_Transcriptomics/analysis/S13-PLS1-Realistic.Rmd, R, 182 lines
2024_NI_Imaging_Transcriptomics/analysis/S14-PLSR_Fit.Rmd, R, 357 lines
2024_NI_Imaging_Transcriptomics/analysis/S15-PLSR-Realistic.Rmd, R, 132 lines
2024_NI_Imaging_Transcriptomics/analysis/S16-Leave-one-region-out.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S17-Combined_null.Rmd, R, 397 lines
2024_NI_Imaging_Transcriptomics/analysis/S18-MoranI.Rmd, R, 170 lines
2024_NI_Imaging_Transcriptomics/analysis/S19-Simulated_GeneSet_size.Rmd, R, 212 lines
2024_NI_Imaging_Transcriptomics/analysis/S2-Moran0.01.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S20-MF_GeneSet_size.Rmd, R, 212 lines
2024_NI_Imaging_Transcriptomics/analysis/S21-Main_Analysis_with_rnorm.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S3-MF.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S4-Rdonor0.2.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S5-Coexp_matched.Rmd, R, 188 lines
2024_NI_Imaging_Transcriptomics/analysis/S6-Brain_specific.Rmd, R, 186 lines
2024_NI_Imaging_Transcriptomics/analysis/S7-Shaefer100.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S8-Shaefer200.Rmd, R, 343 lines
2024_NI_Imaging_Transcriptomics/analysis/S9-Realistic.Rmd, R, 182 lines
2024_NI_Imaging_Transcriptomics/analysis/render_rmd_files.R, R, 13 lines
2024_NI_Imaging_Transcriptomics/data/BrainDat/generate_brain.R, R, 167 lines
2024_NI_Imaging_Transcriptomics/data/BrainInfo/extract_centroid/centroid_extraction_sphere.m, MATLAB, 36 lines
2024_NI_Imaging_Transcriptomics/data/BrainInfo/extract_centroid/extract_centroid.m, MATLAB, 20 lines
2024_NI_Imaging_Transcriptomics/data/BrainInfo/extract_centroid/fread3.m, MATLAB, 30 lines
2024_NI_Imaging_Transcriptomics/data/BrainInfo/extract_centroid/read_annotation.m, MATLAB, 183 lines
2024_NI_Imaging_Transcriptomics/data/BrainInfo/extract_centroid/read_surf.m, MATLAB, 147 lines
2024_NI_Imaging_Transcriptomics/data/BrainInfo/perm_id_weights/generate_permID_MoranW.R, R, 195 lines, 1 match
2024_NI_Imaging_Transcriptomics/data/GP_simulated_brain/desikan.py, Python, 66 lines
2024_NI_Imaging_Transcriptomics/data/GP_simulated_brain/functions.py, Python, 334 lines
2024_NI_Imaging_Transcriptomics/data/GP_simulated_brain/schaefer100.py, Python, 66 lines
2024_NI_Imaging_Transcriptomics/data/GP_simulated_brain/schaefer200.py, Python, 66 lines
2024_NI_Imaging_Transcriptomics/data/GeneSets/generate_GeneSets.R, R, 98 lines
2024_NI_Imaging_Transcriptomics/data/sampled_GeneSets/generate_sampled_GeneSets.R, R, 86 lines
2024_NI_Imaging_Transcriptomics/data/sampled_GeneSets/merge_sampled_GeneSets.R, R, 24 lines
2024_NI_Imaging_Transcriptomics/functions/analysis_functions.R, R, 765 lines
2024_NI_Imaging_Transcriptomics/functions/cor_functions.R, R, 455 lines
2024_NI_Imaging_Transcriptomics/functions/data_functions.R, R, 128 lines
2024_NI_Imaging_Transcriptomics/functions/resampling_gene_functions.R, R, 165 lines
2024_NI_Imaging_Transcriptomics/functions/spinning_brain_functions.R, R, 42 lines
2024_NI_Imaging_Transcriptomics/functions/vacc_function.R, R, 113 lines, 2 matches
2024_NI_Imaging_Transcriptomics/misc/analysis_plsr.R, R, 109 lines
2024_NI_Imaging_Transcriptomics/misc/analysis_sim_res_paired.R, R, 216 lines
2024_NI_Imaging_Transcriptomics/misc/analysis_sim_res_single.R, R, 161 lines
2024_NI_Imaging_Transcriptomics/misc/find_odd_brain.R, R, 102 lines, 1 match
2024_NI_Imaging_Transcriptomics/misc/merge_vacc_results.R, R, 31 lines
2024_NI_Imaging_Transcriptomics/misc/pls_test.R, R, 163 lines
2024_NI_Imaging_Transcriptomics/misc/test_code.R, R, 165 lines
2024_NI_Imaging_Transcriptomics/misc/vacc_script.R, R, 71 lines
2024_NI_Imaging_Transcriptomics/results/cp_push.sh, Shell, 25 lines
2025_ORA_Background_Omission/code/1.perform_simulation_aurina2019.R, R, 52 lines
2025_ORA_Background_Omission/code/1.perform_simulation_enigmatoolbox.R, R, 52 lines
2025_ORA_Background_Omission/code/2.process_simulation_results_aurina2019.R, R, 70 lines
2025_ORA_Background_Omission/code/2.process_simulation_results_enigmatoolbox.R, R, 71 lines
2025_ORA_Background_Omission/code/3.scatter_plot_aurina2019.R, R, 86 lines
2025_ORA_Background_Omission/code/3.scatter_plot_enigmatoolbox.R, R, 181 lines
2025_ORA_Background_Omission/code/4.top_terms_aurina2019.R, R, 80 lines
2025_ORA_Background_Omission/code/4.top_terms_enigmatoolbox.R, R, 134 lines
2025_ORA_Background_Omission/code/5.SI_table_enigmatoolbox.R, R, 65 lines
2025_ORA_Background_Omission/code/6.article_analysis.R, R, 361 lines
2025_ORA_Background_Omission/code/functions.R, R, 77 lines
2025_ORA_Background_Omission/code/intersectToList.cpp, C++, 29 lines
README.md, Text, 17 lines

At the source: github.com/zh1peng/paper_code

MICA-MNI/ENIGMA

License: BSD-3-Clause

State: the link answers, verified on 27 September 2026

Evidence: files inventoried

Commit: b08974b55243060cbc1fad12c87048037446e8f7, 15 January 2026

Languages: MATLAB (63), Python (47), Jupyter (5), JavaScript (2)

Size: 1,175 files, 117 scripts

Software Heritage: not archived

Found in: “Data Availability Statement”

Holds: README, license file, environment (environment.yml, environment_all_py3.10.yml, environment_windows.yml, requirements.txt, setup.cfg, setup.py, docs/requirements.txt), continuous integration, documentation, 4 notebooks

Not found: CITATION.cff, tests

Tools: NumPy (19 files), SciPy (7 files), Statistics and Machine Learning Toolbox (5 files), pandas (4 files), scikit-learn (4 files), Matplotlib (3 files), NiBabel (3 files), FreeSurfer (2 files), cifti-matlab (1 file), GIfTI library for MATLAB (1 file), seaborn (1 file)

Availability: 1 check, the latest on 27 September 2026: the link answers

27 September 2026: the link answers

119 files

docs/_static/jquery.js, JavaScript, 4 lines
docs/_static/js/copybutton.js, JavaScript, 65 lines
docs/conf.py, Python, 95 lines
docs/source/.ipynb_checkpoints/Untitled-checkpoint.ipynb, Jupyter, 1 line
enigmatoolbox/__init__.py, Python, 4 lines
enigmatoolbox/_version.py, Python, 3 lines
enigmatoolbox/cross_disorder/__init__.py, Python, 3 lines
enigmatoolbox/cross_disorder/cross_disorder.py, Python, 120 lines
enigmatoolbox/datasets/__init__.py, Python, 23 lines
enigmatoolbox/datasets/base.py, Python, 1,789 lines
enigmatoolbox/histology/__init__.py, Python, 5 lines
enigmatoolbox/histology/base.py, Python, 345 lines
enigmatoolbox/mesh/__init__.py, Python, 9 lines
enigmatoolbox/mesh/array_operations.py, Python, 947 lines
enigmatoolbox/mesh/mesh_correspondence.py, Python, 92 lines
enigmatoolbox/mesh/mesh_creation.py, Python, 105 lines
enigmatoolbox/mesh/mesh_elements.py, Python, 744 lines
enigmatoolbox/mesh/mesh_io.py, Python, 166 lines
enigmatoolbox/mesh/mesh_operations.py, Python, 523 lines
enigmatoolbox/permutation_testing/__init__.py, Python, 8 lines
enigmatoolbox/permutation_testing/permutation_testing.py, Python, 879 lines
enigmatoolbox/plotting/__init__.py, Python, 7 lines
enigmatoolbox/plotting/base.py, Python, 502 lines
enigmatoolbox/plotting/colormaps.py, Python, 97 lines
enigmatoolbox/plotting/defaults_plotting.py, Python, 55 lines
enigmatoolbox/plotting/sphinx_gallery_scrapper.py, Python, 45 lines
enigmatoolbox/plotting/surface_plotting.py, Python, 779 lines
enigmatoolbox/plotting/utils.py, Python, 371 lines
enigmatoolbox/plotting/utils_qt.py, Python, 17 lines
enigmatoolbox/utils/__init__.py, Python, 10 lines
enigmatoolbox/utils/parcellation.py, Python, 375 lines
enigmatoolbox/utils/useful.py, Python, 57 lines
enigmatoolbox/vtk_interface/__init__.py, Python, 14 lines
enigmatoolbox/vtk_interface/checks.py, Python, 142 lines
enigmatoolbox/vtk_interface/decorators.py, Python, 300 lines
enigmatoolbox/vtk_interface/io_support/__init__.py, Python, 8 lines
enigmatoolbox/vtk_interface/io_support/freesurfer_support.py, Python, 245 lines
enigmatoolbox/vtk_interface/io_support/gifti_support.py, Python, 141 lines
enigmatoolbox/vtk_interface/pipeline.py, Python, 344 lines
enigmatoolbox/vtk_interface/wrappers/__init__.py, Python, 77 lines
enigmatoolbox/vtk_interface/wrappers/actor.py, Python, 323 lines
enigmatoolbox/vtk_interface/wrappers/algorithm.py, Python, 341 lines
enigmatoolbox/vtk_interface/wrappers/base.py, Python, 611 lines
enigmatoolbox/vtk_interface/wrappers/data_object.py, Python, 554 lines
enigmatoolbox/vtk_interface/wrappers/lookup_table.py, Python, 82 lines
enigmatoolbox/vtk_interface/wrappers/misc.py, Python, 108 lines
enigmatoolbox/vtk_interface/wrappers/property.py, Python, 30 lines
enigmatoolbox/vtk_interface/wrappers/renderer.py, Python, 265 lines
enigmatoolbox/vtk_interface/wrappers/utils.py, Python, 209 lines
matlab/scripts/ahba/fetch_ahba.m, MATLAB, 34 lines
matlab/scripts/ahba/risk_genes.m, MATLAB, 108 lines
matlab/scripts/example_data/load_example_data.m, MATLAB, 24 lines
matlab/scripts/histology/bb_gradient_plot.m, MATLAB, 122 lines
matlab/scripts/histology/bb_moments_raincloud.m, MATLAB, 101 lines
matlab/scripts/histology/economo_koskinas_spider.m, MATLAB, 279 lines
matlab/scripts/import_export/write_cifti.m, MATLAB, 44 lines
matlab/scripts/load_connectivity/load_fc.m, MATLAB, 38 lines
matlab/scripts/load_connectivity/load_fc_as_one.m, MATLAB, 34 lines
matlab/scripts/load_connectivity/load_sc.m, MATLAB, 38 lines
matlab/scripts/load_connectivity/load_sc_as_one.m, MATLAB, 34 lines
matlab/scripts/permutation_testing/centroid_extraction_sphere.m, MATLAB, 67 lines
matlab/scripts/permutation_testing/perm_sphere_p.m, MATLAB, 76 lines
matlab/scripts/permutation_testing/rotate_parcellation.m, MATLAB, 135 lines
matlab/scripts/permutation_testing/shuf_test.m, MATLAB, 93 lines
matlab/scripts/permutation_testing/spin_test.m, MATLAB, 83 lines
matlab/scripts/plotting/enigma_scatter.m, MATLAB, 80 lines
matlab/scripts/structural_covariance/structural_covariance.m, MATLAB, 32 lines
matlab/scripts/summary_statistics/cross_disorder_effect.m, MATLAB, 137 lines
matlab/scripts/summary_statistics/load_summary_stats.m, MATLAB, 159 lines
matlab/scripts/surface_viewer/getaffine.m, MATLAB, 34 lines
matlab/scripts/surface_viewer/nfaces.m, MATLAB, 29 lines
matlab/scripts/surface_viewer/plot_cortical.m, MATLAB, 119 lines
matlab/scripts/surface_viewer/plot_subcortical.m, MATLAB, 145 lines
matlab/scripts/useful/parcel_to_surface.m, MATLAB, 65 lines
matlab/scripts/useful/read_annotation.m, MATLAB, 129 lines
matlab/scripts/useful/reorder_sctx.m, MATLAB, 27 lines
matlab/scripts/useful/surface_to_parcel.m, MATLAB, 34 lines
matlab/scripts/useful/zscore_matrix.m, MATLAB, 42 lines
matlab/shared/colormaps/Blues.m, MATLAB, 267 lines
matlab/shared/colormaps/Blues_r.m, MATLAB, 267 lines
matlab/shared/colormaps/Greys.m, MATLAB, 267 lines
matlab/shared/colormaps/GyBu.m, MATLAB, 267 lines
matlab/shared/colormaps/GyBu_r.m, MATLAB, 267 lines
matlab/shared/colormaps/GyRd.m, MATLAB, 267 lines
matlab/shared/colormaps/GyRd_r.m, MATLAB, 267 lines
matlab/shared/colormaps/RdBu.m, MATLAB, 267 lines
matlab/shared/colormaps/RdBu_r.m, MATLAB, 267 lines
matlab/shared/colormaps/Reds.m, MATLAB, 267 lines
matlab/shared/colormaps/Reds_r.m, MATLAB, 267 lines
matlab/shared/colormaps/TealRd.m, MATLAB, 256 lines
matlab/shared/colormaps/eco_kos.m, MATLAB, 17 lines
matlab/shared/colormaps/fake_parula.m, MATLAB, 76 lines
matlab/shared/colormaps/inferno.m, MATLAB, 269 lines
matlab/shared/colormaps/magma.m, MATLAB, 271 lines
matlab/shared/colormaps/plasma.m, MATLAB, 270 lines
matlab/shared/colormaps/romaO.m, MATLAB, 267 lines
matlab/shared/colormaps/romaO_r.m, MATLAB, 268 lines
matlab/shared/colormaps/viridis.m, MATLAB, 267 lines
matlab/shared/import_export/import_export_testing.m, MATLAB, 44 lines
matlab/shared/surfstat/SurfStatAvSurf.m, MATLAB, 44 lines
matlab/shared/surfstat/SurfStatDataCursor.m, MATLAB, 17 lines
matlab/shared/surfstat/SurfStatReadData.m, MATLAB, 113 lines
matlab/shared/surfstat/SurfStatReadData1.m, MATLAB, 63 lines
matlab/shared/surfstat/SurfStatReadSurf.m, MATLAB, 133 lines
matlab/shared/surfstat/SurfStatReadSurf1.m, MATLAB, 164 lines
matlab/shared/surfstat/SurfStatWriteData.m, MATLAB, 41 lines
matlab/shared/surfstat/SurfStatWriteSurf.m, MATLAB, 81 lines
matlab/shared/surfstat/SurfStatWriteSurf1.m, MATLAB, 96 lines
matlab/shared/surfstat/SurfStatWriteSurf1_nonorm.m, MATLAB, 83 lines
matlab/shared/surfstat/colorbar_range.m, MATLAB, 37 lines
matlab/shared/surfstat/enigma_colormap.m, MATLAB, 106 lines
matlab/shared/useful/chop.m, MATLAB, 29 lines
poster-figures/Untitled.ipynb, Jupyter, 11 lines
poster-figures/antisocial.ipynb, Jupyter, 2 lines
poster-figures/epilepsy.ipynb, Jupyter, 44 lines
poster-figures/figures.ipynb, Jupyter, 35 lines
setup.py, Python, 81 lines
LICENSE, License, 29 lines
README.rst, Text, 106 lines

At the source: github.com/MICA-MNI/ENIGMA

The paper's code and data availability statement is in the Data section.

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:

3 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
382 scripts, each with its path and the digest of its content;
4 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

Datasets cited

db.humanconnectome.org/-, at Human Connectome Project; found in “Data Availability Statement”

Availability statements

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

they point to a dataset: db.humanconnectome.org/-
they point to the authors' code: MICA-MNI/ENIGMA, YuLab-SMU/enrichplot, zh1peng/paper_code

Read them in the paper: doi.org/10.1002/hbm.70605.

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 7 keywords, 8 MeSH terms, 3 funders, 72 references.

Cite

This paper

Cao, Z., Yuan, D., Qin, J., Wu, Y., Li, C., & Zhan, G. (2026). BrainEnrich: Revealing Biological Insights for Imaging-Derived Phenotypes Through Transcriptomic Enrichment. Human brain mapping, 47(10), e70605. https://doi.org/10.1002/hbm.70605

BibTeX

@article{cao2026brainenrich, author = {Cao, Zhipeng and Yuan, Dekang and Qin, Jinmei and Wu, Yujie and Li, Chenhu and Zhan, Guilai}, title = {{BrainEnrich: Revealing Biological Insights for Imaging-Derived Phenotypes Through Transcriptomic Enrichment}}, journal = {Human brain mapping}, year = {2026}, month = jul, volume = {47}, number = {10}, pages = {e70605}, publisher = {Wiley}, issn = {1065-9471}, doi = {10.1002/hbm.70605}, url = {https://doi.org/10.1002/hbm.70605}, pmid = {42438110}, pmcid = {PMC13357997} }

RIS

TY - JOUR AU - Cao, Zhipeng AU - Yuan, Dekang AU - Qin, Jinmei AU - Wu, Yujie AU - Li, Chenhu AU - Zhan, Guilai TI - BrainEnrich: Revealing Biological Insights for Imaging-Derived Phenotypes Through Transcriptomic Enrichment T2 - Human brain mapping J2 - Hum Brain Mapp PY - 2026 DA - 2026/07/01 VL - 47 IS - 10 SP - e70605 SN - 1065-9471 PB - Wiley DO - 10.1002/hbm.70605 UR - https://doi.org/10.1002/hbm.70605 LA - en ER -

CSL-JSON

{ "id": "10.1002/hbm.70605", "type": "article-journal", "title": "BrainEnrich: Revealing Biological Insights for Imaging-Derived Phenotypes Through Transcriptomic Enrichment", "container-title": "Human brain mapping", "author": [ { "family": "Cao", "given": "Zhipeng" }, { "family": "Yuan", "given": "Dekang" }, { "family": "Qin", "given": "Jinmei" }, { "family": "Wu", "given": "Yujie" }, { "family": "Li", "given": "Chenhu" }, { "family": "Zhan", "given": "Guilai" } ], "container-title-short": "Hum Brain Mapp", "volume": "47", "issue": "10", "page": "e70605", "DOI": "10.1002/hbm.70605", "PMID": "42438110", "PMCID": "PMC13357997", "ISSN": "1065-9471", "publisher": "Wiley", "URL": "https://doi.org/10.1002/hbm.70605", "language": "en", "issued": { "date-parts": [ [ 2026, 7, 1 ] ] } }

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