The scDRS application implements an approach that links scRNA-seq with polygenic disease risk at single-cell resolution, independent of annotated cell types. scDRS identifies cells exhibiting excess expression across disease-associated genes implicated by genome-wide association studies (GWASs). Genes whose expression was correlated with the scDRS score across cells (reflecting coexpression with GWAS disease-associated genes) were strongly enriched for gold-standard drug target and Mendelian disease genes.

References:

• Martin Jinye Zhang, Kangcheng Hou, Kushal K. Dey, Saori Sakaue, Karthik A. Jagadeesh, Kathryn Weinand, Aris Taychameekiatchai, Poorvi Rao, Angela Oliveira Pisco, James Zou, Bruce Wang, Michael Gandal, Soumya Raychaudhuri, Bogdan Pasaniuc &iamp; Alkes L. Price
  Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data
  Nature Genetics 54, pages 1572–1580 (2022).

• scDRS GitHub page
• scDRS Documentation

• Module Name: scdrs (see the modules page for more information)
• Unusual environment variables set
  • SCDRS_HOME  installation directory
  • SCDRS_BIN       executable directory
  • SCDRS_SRC       source code directory
  • SCDRS_DATA  sample data directory

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive --mem=4g
[user@cn0911 ~]$module load scdrs   
[+] Loading singularity  3.10.5  on cn4185
[+] Loading scdrs  1.02 
[user@cn0911 ~]$mkdir /data/$USER/scDRS && cd /data/$USER/scDRS
[user@cn0911 ~]$wget https://figshare.com/ndownloader/files/34300925 -O data.zip
[user@cn0911 ~]$unzip data.zip && \
                   mkdir -p data/ && \
                   mv single_cell_data/zeisel_2015/* data/ && \
                   rm data.zip && rm -r single_cell_data
[user@cn0911 ~]$scdrs compute-score \
                         --h5ad-file data/expr.h5ad \
                         --h5ad-species mouse \
                         --gs-file data/geneset.gs \
                         --gs-species mouse \
                         --cov-file data/cov.tsv \
                         --flag-filter-data True \
                         --flag-raw-count True \
                         --flag-return-ctrl-raw-score False \
                         --flag-return-ctrl-norm-score True \
                         --out-folder data/

Loading data:
--h5ad-file loaded: n_cell=3005, n_gene=13572 (sys_time=1.7s)
First 3 cells: ['1772071015_C02', '1772071017_G12', '1772071017_A05']
First 5 genes: ['Tspan12', 'Tshz1', 'Fnbp1l', 'Adamts15', 'Cldn12']
--cov-file loaded: covariates=['const', 'n_genes'] (sys_time=1.7s)
First 5 values for 'const': [1, 1, 1, 1, 1]
First 5 values for 'n_genes': [4848, 4685, 6028, 5824, 4701]
--gs-file loaded: n_trait=29 (sys_time=1.8s)
Print info for first 3 traits:
First 3 elements for 'PASS_ADHD_Demontis2018': ['St3gal3', 'Kdm4a', 'Ptprf'], [6.4588, 6.2164, 5.8681]
First 3 elements for 'PASS_Alzheimers_Jansen2019': ['Ms4a6d', 'Clu', 'Picalm'], [7.1313, 7.066, 6.6287]
First 3 elements for 'PASS_BIP_Mullins2021': ['Trank1', 'Myrf', 'Fads1'], [7.2182, 7.0688, 6.9447]

Preprocessing:

Computing scDRS score:
Computing control scores: 100%|█████████████████████████████████████████████| 1000/1000 [00:53<00:00, 18.74it/s]
Trait=PASS_ADHD_Demontis2018, n_gene=688: 2/3005 FDR<0.1 cells, 4/3005 FDR<0.2 cells (sys_time=82.3s)
Computing control scores: 100%|███████████████████████████████████████████████████| 1000/1000 [00:49<00:00, 20.27it/s]
Trait=PASS_Alzheimers_Jansen2019, n_gene=630: 0/3005 FDR<0.1 cells, 0/3005 FDR<0.2 cells (sys_time=155.8s)
Computing control scores: 100%|███████████████████████████████████████████████████| 1000/1000 [00:58<00:00, 17.24it/s]
Trait=PASS_BIP_Mullins2021, n_gene=776: 171/3005 FDR<0.1 cells, 314/3005 FDR<0.2 cells (sys_time=238.8s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:54<00:00, 18.34it/s]
Trait=PASS_BIP_Stahl2019, n_gene=716: 77/3005 FDR<0.1 cells, 186/3005 FDR<0.2 cells (sys_time=317.8s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:52<00:00, 18.89it/s]
Trait=PASS_DrinksPerWeek_Liu2019, n_gene=694: 0/3005 FDR<0.1 cells, 0/3005 FDR<0.2 cells (sys_time=394.5s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:53<00:00, 18.66it/s]
Trait=PASS_GeneralRiskTolerance_KarlssonLinner2019, n_gene=700: 173/3005 FDR<0.1 cells, 314/3005 FDR<0.2 cells (sys_time=472.5s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:54<00:00, 18.43it/s]
Trait=PASS_Insomnia_Jansen2019, n_gene=710: 0/3005 FDR<0.1 cells, 1/3005 FDR<0.2 cells (sys_time=550.9s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:55<00:00, 17.93it/s]
Trait=PASS_Intelligence_SavageJansen2018, n_gene=742: 170/3005 FDR<0.1 cells, 299/3005 FDR<0.2 cells (sys_time=631.0s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:54<00:00, 18.34it/s]
Trait=PASS_MDD_Howard2019, n_gene=716: 281/3005 FDR<0.1 cells, 434/3005 FDR<0.2 cells (sys_time=709.5s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:55<00:00, 18.07it/s]
Trait=PASS_ReactionTime_Davies2018, n_gene=733: 73/3005 FDR<0.1 cells, 191/3005 FDR<0.2 cells (sys_time=789.6s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:53<00:00, 18.81it/s]
Trait=PASS_SWB, n_gene=690: 292/3005 FDR<0.1 cells, 466/3005 FDR<0.2 cells (sys_time=867.2s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:56<00:00, 17.63it/s]
Trait=PASS_Schizophrenia_Pardinas2018, n_gene=756: 178/3005 FDR<0.1 cells, 320/3005 FDR<0.2 cells (sys_time=948.2s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:54<00:00, 18.37it/s]
Trait=PASS_SleepDuration_Dashti2019, n_gene=718: 104/3005 FDR<0.1 cells, 208/3005 FDR<0.2 cells (sys_time=1026.9s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:56<00:00, 17.66it/s]
Trait=PASS_VerbalNumericReasoning_Davies2018, n_gene=749: 157/3005 FDR<0.1 cells, 305/3005 FDR<0.2 cells (sys_time=1108.0s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:55<00:00, 18.05it/s]
Trait=PASS_Worry_Nagel2018, n_gene=733: 179/3005 FDR<0.1 cells, 285/3005 FDR<0.2 cells (sys_time=1187.8s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:56<00:00, 17.72it/s]
Trait=UKB_460K.body_BMIz, n_gene=751: 182/3005 FDR<0.1 cells, 339/3005 FDR<0.2 cells (sys_time=1269.0s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:52<00:00, 19.18it/s]
Trait=UKB_460K.body_HEIGHTz, n_gene=671: 0/3005 FDR<0.1 cells, 6/3005 FDR<0.2 cells (sys_time=1345.0s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:55<00:00, 17.86it/s]
Trait=UKB_460K.cov_EDU_COLLEGE, n_gene=743: 197/3005 FDR<0.1 cells, 338/3005 FDR<0.2 cells (sys_time=1425.2s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:54<00:00, 18.24it/s]
Trait=UKB_460K.cov_EDU_YEARS, n_gene=729: 239/3005 FDR<0.1 cells, 403/3005 FDR<0.2 cells (sys_time=1504.2s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:54<00:00, 18.27it/s]
Trait=UKB_460K.cov_SMOKING_STATUS, n_gene=725: 194/3005 FDR<0.1 cells, 360/3005 FDR<0.2 cells (sys_time=1583.4s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:55<00:00, 17.87it/s]
Trait=UKB_460K.mental_NEUROTICISM, n_gene=751: 229/3005 FDR<0.1 cells, 401/3005 FDR<0.2 cells (sys_time=1663.7s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:53<00:00, 18.65it/s]
Trait=UKB_460K.other_MORNINGPERSON, n_gene=712: 172/3005 FDR<0.1 cells, 320/3005 FDR<0.2 cells (sys_time=1741.3s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:52<00:00, 18.99it/s]
Trait=UKB_460K.repro_NumberChildrenEverBorn_Pooled, n_gene=695: 43/3005 FDR<0.1 cells, 86/3005 FDR<0.2 cells (sys_time=1817.8s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:24<00:00, 41.63it/s]
Trait=spatial_ventral, n_gene=228: 672/3005 FDR<0.1 cells, 770/3005 FDR<0.2 cells (sys_time=1859.7s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:19<00:00, 51.75it/s]
Trait=spatial_dorsal, n_gene=155: 549/3005 FDR<0.1 cells, 641/3005 FDR<0.2 cells (sys_time=1895.8s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 76.27it/s]
Trait=spatial_distal, n_gene=41: 3/3005 FDR<0.1 cells, 10/3005 FDR<0.2 cells (sys_time=1923.2s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:16<00:00, 61.84it/s]
Trait=spatial_proximal, n_gene=98: 219/3005 FDR<0.1 cells, 356/3005 FDR<0.2 cells (sys_time=1954.9s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:17<00:00, 56.28it/s]
Trait=spatial_deep, n_gene=122: 484/3005 FDR<0.1 cells, 576/3005 FDR<0.2 cells (sys_time=1988.6s)
Computing control scores: 100%|███████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.87it/s]
Trait=spatial_superficial, n_gene=55: 190/3005 FDR<0.1 cells, 322/3005 FDR<0.2 cells (sys_time=2016.9s)
[user@cn0911 ~]$exit

[user@cn0911 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$