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DOI

This repository contains data and code for the paper Zhang*, Hou*, et al. Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data.

Also see scDRS software and documentation.

Versions

Subset of code and data to reproduce main results of the paper

Codes are at ./job.reproduce. To run the code, set DATA_PATH (if in the code) to your local folder of the main data scDRS_data_release_{RELEASE_DATE} and set SCORE_FILE_PATH (if in the code) to your local folder of the scDRS score files scDRS_data_release_{RELEASE_DATE}.score_file_tmsfacs.

Compute scDRS scores for TMS FACS + 74 diseases/traits

  • Final version (rv_final) and revision 1 (rv1): Score files are in scDRS_data_release_030122.score_file_tmsfacs. Compute them yourself using reproduce_compute_score.tms_facs_with_cov.magma_10kb_1000.rv1.sh
  • Initial submission: Score files were included in scDRS_data_release_092121.score_file_tmsfacs. Compute them yourself using reproduce_compute_score.tms_facs_with_cov.magma_10kb_1000.sh

Cell type-level analysis (Fig. 3)

  • Final version (rv_final) and revision 1 (rv1): reproduce_celltype.rv1.ipynb.
  • Initial submission: reproduce_celltype.ipynb.

T cell analysis (Fig. 4)

  • Final version (rv_final) and revision 1 (rv1) (Fig. 4A-E): reproduce_tcell.rv1.ipynb.
  • Initial submission (Fig. 4A-C): reproduce_tcell.ipynb.

T cell gene prioritization (Fig. 4)

  • Final version (rv_final) and revision 1 (rv1) (Fig. 4F): reproduce_tcell_gene.rv1.ipynb.
  • Initial submission (Fig. 4D): reproduce_tcell_gene.ipynb.

Neuron analysis (Fig. 5A,B)

  • Final version (rv_final) and revision 1 (rv1): reproduce_neuron.rv1.ipynb.
  • Initial submission: reproduce_neuron.ipynb.

Hepatocyte analysis (Fig. 5C,D)

  • Final version (rv_final) and revision 1 (rv1): reproduce_hep.rv1.ipynb.
  • Initial submission: reproduce_hep.ipynb.

Complete code

Data curation: job.curate_data

Curate information for 74 diseases/traits:

  • Curate information for the 74 diseases: job.curate_data/get_trait_list.ipynb
  • Curate information for the 74 diseases (rv1): job.curate_data/get_trait_list.rv1.ipynb

Curate gene set (.gs) files:

  • .gs file for 74 diseases: job.curate_data/curate_gs_file.ipynb
  • .gs file for 74 diseases (rv1): job.curate_data/curate_gs_file.rv1.ipynb
  • .gs file for T cell signatures: job.curate_data/curate_gs.tcell_signature.ipynb
  • .gs file for ploidy signatures: job.curate_data/curate_ploidy_gs.ipynb
  • .gs file for zonation signatures: job.curate_data/curate_zonation_gs.ipynb
  • .gs file for metabolic pathways: job.curate_data/curate_gs.metabolic.ipynb

Curate scRNA-seq data sets:

  • TS FACS: job.curate_data/curate_ts_data.ipynb
  • Cano-Gamez & Soskic et al.: job.curate_data/curate_canogamez_tcell_data.ipynb
  • Nathan et al.: job.curate_data/curate_nathan_tcell_data.ipynb
  • Aizarani et al.: job.curate_data/curate_aizarani_liver_atlas_data.ipynb
  • Halpern & Shenhav et al.: job.curate_data/curate_halpern_mouse_liver_data.ipynb
  • Richter & Deligiannis et al.: job.curate_data/curate_richter_hepatocyte_data.ipynb
  • Compute gene-level statistics: compute_data_stats.py and compute_data_stats.sh
  • Get meta information of data sets: get_data_info.ipynb
  • Get meta information of data sets (rv1): get_data_info.rv1.ipynb
  • Get meta information of data sets (rv_final): get_data_info.rv_final.ipynb

Compute scDRS scores: job.compute_score

  • TMS FACS + 74 diseases: job.compute_score/compute_score.tms_facs_with_cov.magma_10kb_1000.sh
  • TMS FACS + T cell signatures (using scDRS scripts instead of CLI): job.compute_score/compute_score.tms_facs_with_cov.tcell_sig.sh
  • TMS FACS + metabolic (using scDRS scripts instead of CLI): job.compute_score/compute_score.tms_facs_with_cov.hep_metabolic.sh
  • TMS droplet + 74 diseases: job.compute_score/compute_score.tms_droplet_with_cov.magma_10kb_1000.sh
  • TS FACS + 74 diseases: job.compute_score/compute_score.ts_facs_with_cov.magma_10kb_1000.sh

Scehma (Fig. 1): job.schema

Make schematic figures.

Simulation (Fig. 2): job.simulation

Data generation:

  • Generate the TMS FACS 10K subsampled data and null gene sets: job.simulation/generate_null_simulation_data.ipynb
  • Generate the TMS FACS 10K subsampled data and null gene sets (rv1): job.simulation/generate_null_simulation_data.rv1.ipynb
  • Generate location-matched gene sets and make figures (rv1): job.simulation/simulation.other_null.ipynb
  • Generate location-matched gene sets and make figures (rv_final): job.simulation/simulation.other_null.rv_final.ipynb
  • Generate causal gene sets and perturbation configurations: job.simulation/generate_causal_simulation_data.ipynb
  • Generate 20 reps of subsampled TMS FACS 10K data (rv1): job.simulation/generate_subsampled_tms_data.rv1.ipynb

Compute results:

  • Compute scDRS scores for null simulations: job.simulation/compute_simu_score.sh
  • Compute scDRS scores for null simulations (rv1): job.simulation/compute_simu_score.rv1.sh
  • Compute scDRS scores for null simulations using the -adj-prop option (rv1): job.simulation/compute_simu_score.adj_prop.rv1.sh
  • Compute Seurat scores for null simulations: job.simulation/compute_simu_score_scanpy.sh
  • Compute Seurat scores for null simulations (rv1): job.simulation/compute_simu_score_scanpy.rv1.sh
  • Compute Vision scores for null simulations: job.simulation/compute_simu_score_vision.sh
  • Compute Vision scores for null simulations (rv1): job.simulation/compute_simu_score_vision.rv1.sh
  • Compute VAM scores for null simulations: job.simulation/call_R_vam.sh
  • Compute VAM scores for null simulations (rv1): job.simulation/call_R_vam.rv1.sh
  • Compute scores (scDRS/Seurat/Vision) for causal simulations (500 random causal cells): job.simulation/compute_perturb_simu_score.sh
  • Compute scores (scDRS/Seurat/Vision) for causal simulations (B cells causal): job.simulation/compute_perturb_simu_score_Bcell.sh

Make figures:

  • Make figures for null simulations: job.simulation/make_figure.null_simulation.ipynb
  • Make figures for null simulations (rv1): job.simulation/make_figure.null_simulation.rv1.ipynb
  • Make figures for null simulations (rv_final): job.simulation/make_figure.null_simulation.rv_final.ipynb
  • Make figures for causal simulations (500 random causal cells): job.simulation/make_figure.causal_simulation.ipynb
  • Make figures for causal simulations (500 random causal cells) (rv_final): job.simulation/make_figure.causal_simulation.rv_final.ipynb
  • Make figures for causal simulations (B cells causal): job.simulation/make_figure.causal_simulation_Bcell.ipynb
  • Make figures for causal simulations (B cells causal) (rv_final): job.simulation/make_figure.causal_simulation_Bcell.rv_final.ipynb
  • Make figures for subsampled UKB (rv1): job.simulation/make_figure.UKB_subsample.rv1.ipynb
  • Make figures for subsampled UKB (rv_final): job.simulation/make_figure.UKB_subsample.rv_final.ipynb

Cell type-level results (Fig. 3): job.celltype_association

  • Summary of the cell-type association results: job.celltype_association/summary_ct.ipynb
  • Main analysis: job.celltype_association/main_figure.ipynb
  • Main analysis (rv1): job.celltype_association/main_figure.rv1.ipynb
  • Comparison of cell-type association for three atlas datasets: TMS FACS, TMS droplet, TS FACS: job.celltype_association/atlas_compare.ipynb
  • Comparison of cell-type association for three atlas datasets: TMS FACS, TMS droplet, TS FACS (rv1): job.celltype_association/atlas_compare.rv1.ipynb
  • Relationship between scDRS power and heritability, polygenicity: job.celltype_association/optimal_param.ipynb
  • Comparison of cell-type association to LDSC-SEG: job.celltype_association/ldsc_compare.ipynb
  • Comparison of cell-type association to alternative methods (rv1): job.celltype_association/methods_compare.rv1.ipynb
  • Effects of gene sets for scDRS power: job.celltype_association/vary_geneset.ipynb
  • Examples of within-cell-type heterogeneity (including correlated genes and covariates) (rv_final): job.celltype_association/hetero_examples.rv_final.ipynb:
  • Evaluation of alternative versions of scDRS using control traits and cell types (rv1): job.continuous_score/ (see the directory for more details)

T cell example (Fig. 4): job.case_tcell

  • Reprocess TMS T cells and assign effectorness gradients: job.case_tcell/s1_reprocess_tms_tcell.ipynb
  • Main analysis: job.case_tcell/s3_analysis_tcell.ipynb
  • Main analysis (rv1): job.case_tcell/s3_analysis_tcell.rv1.ipynb
  • Main analysis (rv_final): job.case_tcell/s3_analysis_tcell.rv_final.ipynb
  • Replication in Cano-Gamez & Soskic et al. and Nathan et al. data: job.case_tcell/s4_analysis_tcell.replication.ipynb
  • Replication in Cano-Gamez & Soskic et al. and Nathan et al. data (rv1): job.case_tcell/s4_analysis_tcell.replication.rv1.ipynb
  • Cluster-level LDSC-SEG analysis: job.case_tcell/s5_compare_ldsc_cluster_4res.ipynb
  • Cluster-level LDSC-SEG analysis (rv1): job.case_tcell/s5_compare_ldsc_cluster_4res.rv1.ipynb
  • Cluster-level LDSC-SEG analysis (rv_final): job.case_tcell/s5_compare_ldsc_cluster_4res.rv_final.ipynb
  • Disease gene prioritization: job.case_tcell/s6_gene_prioritization.ipynb
  • Disease gene prioritization (rv1): job.case_tcell/s6_gene_prioritization.rv1.ipynb
  • Disease gene prioritization (rv_final): job.case_tcell/s5_compare_ldsc_cluster_4res.rv_final.ipynb
  • Gene set overlap and disease score correlation between traits (rv1): job.case_tcell/s7_contrast_traits.rv1.ipynb
  • Automatic annotation using ProjecTILE in R (rv1): job.case_tcell/s8_map_tms_tcell_ProjecTILs.rv1.ipynb

Neuron example (Fig. 5AB): job.ca1_pyramidal

  • Main analysis (Fig. 5AB): job.ca1_pyramidal/main_figure.ipynb
  • Main analysis (Fig. 5AB) (rv1): job.ca1_pyramidal/main_figure.rv1.ipynb
  • Analysis of neurons in TMS FACS dataset: job.ca1_pyramidal/tms.ipynb
  • Analysis of neurons in TMS FACS dataset (rv1): job.ca1_pyramidal/tms.rv1.ipynb
  • Analysis of Zeisel et al. 2015 dataset: job.ca1_pyramidal/zeisel.ipynb
  • Analysis of Zeisel et al. 2015 dataset (rv1): job.ca1_pyramidal/zeisel.rv1.ipynb
  • Verification of the inferred spatial coordinates: job.ca1_pyramidal/spatial_verify.ipynb

Hepatocyte example (Fig. 5CD): job.case_hepatocyte

  • Reprocess TMS hepatocytes: job.case_hepatocyte/s1_reprocess_tms_hep.ipynb
  • Main analysis: job.case_hepatocyte/s3_analysis_hep.ipynb
  • Main analysis (rv1): job.case_hepatocyte/s3_analysis_hep.rv1.ipynb
  • Main analysis (rv_final): job.case_hepatocyte/s3_analysis_hep.rv_final.ipynb