TensoorQTL leverages general-purpose libraries and graphics processing units (GPUs) to achieve high efficiency of computations at low costR. Using PyTorch or TensorFlow it allows > 200-fold decreases in runtime and ~ 5–10-fold reductions in cost when running on GPUs relative to CPUs.
Allocate an interactive session and run the program. Sample session:
[user@biowulf]$ sinteractive --mem=24g --gres=gpu:p100:1,lscratch:50 -c8 [user@cn4199 ~]$ module load TensorQTL [+] Loading singularity 3.8.5-1 [+] Loading cuDNN/7.6.5/CUDA-10.2 libraries... [+] Loading CUDA Toolkit 10.2.89 ... [+] Loading TensorQTL 1.0.7 ...Usage:
[user@cn4199 ~]$ tensorqtl -h
usage: tensorqtl [-h] [--mode {cis,cis_nominal,cis_independent,cis_susie,trans}] [--covariates COVARIATES]
[--permutations PERMUTATIONS] [--interaction INTERACTION] [--cis_output CIS_OUTPUT]
[--phenotype_groups PHENOTYPE_GROUPS] [--window WINDOW] [--pval_threshold PVAL_THRESHOLD]
[--maf_threshold MAF_THRESHOLD] [--maf_threshold_interaction MAF_THRESHOLD_INTERACTION] [--return_dense]
[--return_r2] [--best_only] [--output_text] [--batch_size BATCH_SIZE] [--load_split] [--warn_monomorphic]
[--fdr FDR] [--qvalue_lambda QVALUE_LAMBDA] [--seed SEED] [-o OUTPUT_DIR]
genotype_path phenotype_bed prefix
tensorQTL: GPU-based QTL mapper
positional arguments:
genotype_path Genotypes in PLINK format
phenotype_bed Phenotypes in BED format
prefix Prefix for output file names
optional arguments:
-h, --help show this help message and exit
--mode {cis,cis_nominal,cis_independent,cis_susie,trans}
Mapping mode. Default: cis
--covariates COVARIATES
Covariates file, tab-delimited, covariates x samples
--permutations PERMUTATIONS
Number of permutations. Default: 10000
--interaction INTERACTION
Interaction term(s)
--cis_output CIS_OUTPUT
Output from 'cis' mode with q-values. Required for independent cis-QTL mapping.
--phenotype_groups PHENOTYPE_GROUPS
Phenotype groups. Header-less TSV with two columns: phenotype_id, group_id
--window WINDOW Cis-window size, in bases. Default: 1000000.
--pval_threshold PVAL_THRESHOLD
Output only significant phenotype-variant pairs with a p-value below threshold. Default: 1e-5 for
trans-QTL
--maf_threshold MAF_THRESHOLD
Include only genotypes with minor allele frequency >= maf_threshold. Default: 0
--maf_threshold_interaction MAF_THRESHOLD_INTERACTION
MAF threshold for interactions, applied to lower and upper half of samples
--return_dense Return dense output for trans-QTL.
--return_r2 Return r2 (only for sparse trans-QTL output)
--best_only Only write lead association for each phenotype (interaction mode only)
--output_text Write output in txt.gz format instead of parquet (trans-QTL mode only)
--batch_size BATCH_SIZE
Batch size. Reduce this if encountering OOM errors.
--load_split Load genotypes into memory separately for each chromosome.
--warn_monomorphic Warn if monomorphic variants are found.
--fdr FDR FDR for cis-QTLs
--qvalue_lambda QVALUE_LAMBDA
lambda parameter for pi0est in qvalue.
--seed SEED Seed for permutations.
-o OUTPUT_DIR, --output_dir OUTPUT_DIR
Output directory
Running the test example:
[user@cn4199 ~]$ cp $TQTL_DATA/* .
[user@cn4199 ~]$ cp $TQTL_EXAMPLE/*.py .
[user@cn4199 ~]$ python tensorqtl_examples.py &
python tensorqtl_examples.py &[1] 3000
PyTorch 1.12.0+cu102
Pandas 1.4.3
Mapping files: 0%| | 0/3 [00:00<?, ?it/s]
Mapping files: 100%|█████████████████████████████████████████████████████████████████████████████| 3/3 [00:23<00:00, 7.80s/it]
cis-QTL mapping: nominal associations for all variant-phenotype pairs
* 445 samples
* 301 phenotypes
* 26 covariates
nvidia-smi
Mon Oct 3 10:14:00 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.82.01 Driver Version: 470.82.01 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla P100-PCIE... On | 00000000:0D:00.0 Off | Off |
| N/A 29C P0 30W / 250W | 789MiB / 16280MiB | 1% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 3030 C /usr/bin/python3 787MiB |
+-----------------------------------------------------------------------------+
[user@cn2375 TensorQTL]$ * 13369268 variants
* checking phenotypes: 301/301
* Computing associations
Mapping chromosome chr18
processing phenotype 301/301
time elapsed: 0.05 min
* writing output
done.
cis-QTL mapping: empirical p-values for phenotypes
* 445 samples
* 301 phenotypes
* 26 covariates
* 13369268 variants
* using seed 123456
* checking phenotypes: 301/301
* computing permutations
processing phenotype 301/301
Time elapsed: 0.40 min
done.
trans-QTL mapping
* 445 samples
* 19836 phenotypes
* 26 covariates
* 13369268 variants
processing batch 1337/1337
elapsed time: 0.62 min
* 7620376 variants passed MAF >= 0.05 filtering
done.
[user@cn4199 ~]$ exit
salloc.exe: Relinquishing job allocation 59748321
[user@biowulf ~]$