Download the main data scDRS_data_release_092121 (3.6 GB) and scDRS score files for TMS FACS + 74 diseases/traits scDRS_data_release_092121.score_file_tmsfacs (36.3 GB).
Codes are at ./job.reproduce
- Score files were already included in
scDRS_data_release_092121.score_file_tmsfacs
. - You can also compute them yourself by the bash sript
reproduce_compute_score.tms_facs_with_cov.magma_10kb_1000.sh
- Set
DATA_PATH
to your local folder ofscDRS_data_release_092121
(containing TMS FACS data and .gs files) and run the script.
- You can reproduce the results using
reproduce_celltype.ipynb
- Set
DATA_PATH
to your local folder ofscDRS_data_release_092121
and run the notebook.
- You can reproduce the results using
reproduce_tcell.ipynb
- Set
DATA_PATH
to your local folder ofscDRS_data_release_092121
, setSCORE_FILE_PATH
to your local folder ofscDRS_data_release_092121.score_file_tmsfacs
and run the notebook.
- You can reproduce the results using
reproduce_tcell_gene.ipynb
- Set
DATA_PATH
to your local folder ofscDRS_data_release_092121
, setSCORE_FILE_PATH
to your local folder ofscDRS_data_release_092121.score_file_tmsfacs
and run the notebook.
- You can reproduce the results using
reproduce_neuron.ipynb
- Set
DATA_PATH
to your local folder ofscDRS_data_release_092121
and run the notebook.
- You can reproduce the results using
reproduce_neuron.ipynb
- Set
DATA_PATH
to your local folder ofscDRS_data_release_092121
, setSCORE_FILE_PATH
to your local folder ofscDRS_data_release_092121.score_file_tmsfacs
and run the notebook.
Curate information for 74 diseases/traits:
- Curate information for the 74 diseases:
job.curate_data/get_trait_list.ipynb
Curate gene set (.gs) files:
- .gs file for 74 diseases:
job.curate_data/curate_gs_file.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
- TMS FACS + 74 diseases:
job.compute_score/compute_score.tms_facs_with_cov.magma_10kb_1000.sh
- TMS FACS + T cell signatures:
job.compute_score/compute_score.tms_facs_with_cov.tcell_sig.sh
- TMS FACS + metabolic:
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
Make schematic figures.
Data generation:
- Generate the TMS FACS 10K subsampled data and null gene sets:
job.simulation/generate_null_simulation_data.ipynb
- Generate causal gene sets and perturbation configurations:
job.simulation/generate_causal_simulation_data.ipynb
Compute results:
- Compute scDRS scores for null simulations:
job.simulation/compute_simu_score.sh
- Compute Seurat scores for null simulations:
job.simulation/compute_simu_score_scanpy.sh
- Compute Vision scores for null simulations:
job.simulation/compute_simu_score_vision.sh
- Compute VAM scores for null simulations:
job.simulation/call_R_vam.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 causal simulations (500 random causal cells):
job.simulation/make_figure.causal_simulation.ipynb
- Make figures for causal simulations (B cells causal):
job.simulation/make_figure.causal_simulation_Bcell.ipynb
- Summary of the cell-type association results:
job.celltype_association/summary_ct.ipynb
- Main analysis:
job.celltype_association/main_figure.ipynb
- Comparison of cell-type association for three atlas datasets: TMS FACS, TMS droplet, TS FACS:
job.celltype_association/atlas_compare.ipynb
- Relationship between scDRS power and heritability, polygenicity:
job.celltype_association/optim_param.ipynb
- Comparison of cell-type association to LDSC-SEG:
job.celltype_association/ldsc_compare.ipynb
- Effects of gene sets for scDRS power:
job.celltype_association/vary_geneset.ipynb
- 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
- Replication in Cano-Gamez & Soskic et al. and Nathan et al. data:
job.case_tcell/s4_analysis_tcell.replication.ipynb
- Cluster-level LDSC-SEG analysis:
job.case_tcell/s5_compare_ldsc_cluster_4res.ipynb
- Disease gene prioritization:
job.case_tcell/s6_gene_prioritization.ipynb
- Main analysis (Fig. 5AB):
job.ca1_pyramidal/main_figure.ipynb
- Analysis of neurons in TMS FACS dataset:
job.ca1_pyramidal/tms.ipynb
- Analysis of Zeisel et al. 2015 dataset:
job.ca1_pyramidal/zeisel.ipynb
- Verification of the inferred spatial coordinates:
job.ca1_pyramidal/spatial_verify.ipynb
- Reprocess TMS hepatocytes:
job.case_hepatocyte/s1_reprocess_tms_hep.ipynb
- Main analysis:
job.case_hepatocyte/s3_analysis_hep.ipynb