OncodriveCLUSTL: a sequence-based clustering method to identify cancer drivers
OncodriveCLUSTL is a sequence-based clustering algorithm to detect significant clustering signals across genomic regions. It is based based on a local background model derived from the simulation of mutations accounting for the composition of trior penta-nucleotide context substitutions observed in the cohort under study.
References:
- Claudia Arnedo-Pac, Loris Mularoni, Ferran Muinos, Abel Gonzalez-Perez and Nuria Lopez-Bigas,
OncodriveCLUSTL: a sequence-based clustering method to identify cancer drivers
Bioinformatics, 2019 35(22), 4788–4790. doi: 10.1093/bioinformatics/btz501
Documentation
Important Notes
- Module Name: oncodriveCLUSTL (see the modules page for more information)
- Unusual environment variables set
- ODCLUSTL_HOME installation directory
- ODCLUSTL_BIN executable directory
- ODCLUSTL_DATA sample data directory
Interactive job
Interactive jobs should be used for debugging, graphics, or applications that cannot be run as batch jobs.
Allocate an interactive session and run the program. Sample session:
[user@biowulf]$ sinteractive --mem=75g -c20 --gres=lscratch:20
[user@cn3335 ~]$ module load oncodriveCLUSTL
[+] Loading singularity 3.10.5 on cn4338
[+] Loading oncodriveCLUSTL 1.1.1
[user@cn3335 ~]$ oncodriveclustl -h
Usage: oncodriveclustl [OPTIONS]
OncodriveCLUSTL is a sequence based clustering method to identify cancer
drivers across the genome
Args: input_file (str): path to mutations file regions_file (str):
path to input genomic coordinates file output_directory(str): path to
output directory. Output files will be generated in it.
input_signature (str): path to file containing input context based
mutational probabilities. By default (when no input signatures),
OncodriveCLUSTL will calculate them from the mutations input file.
elements_file (str): path to file containing one element per row
(optional) to analyzed the listed elements. By default,
OncodriveCLUSTL analyzes all genomic elements contained in `regions_file`.
elements (str): genomic element symbol (optional). The analysis will be
performed only on the specified GEs. genome (str): genome to use:
'hg38', 'hg19', 'mm10', 'c3h', 'car', 'cast' and 'f344'
element_mutations (int): minimum number of mutations per genomic element
to undertake analysis cluster_mutations (int): minimum number of
mutations to define a cluster smooth_window (int): Tukey kernel
smoothing window length cluster_window (int): clustering window length
kmer (int): context nucleotides to calculate the mutational probabilities
(trinucleotides or pentanucleotides) n_simulations (int): number of
simulations simulation_mode (str): simulation mode
simulation_window (int): window length to simulate mutations
signature_calculation (str): signature calculation, mutation frequencies
(default) or mutation counts normalized by k-mer region counts
signature_group (str): header of the column to group signatures. One
signature will be computed for each group cores (int): number of CPUs
to use seed (int): seed log_level (str): verbosity of the logger
concatenate (bool): flag to calculate clustering on collapsed genomic
regions (e.g., coding regions in a gene) clustplot (bool): flag to
generate a needle plot with clusters for an element qqplot (bool):
flat to generate a quantile-quantile (QQ) plot for a dataset gzip
(bool): flag to generate GZIP compressed output files
Returns: None
Options:
-i, --input-file PATH File containing somatic mutations
[required]
-r, --regions-file PATH File with the genomic regions to analyze
[required]
-o, --output-directory TEXT Output directory to be created [required]
-sig, --input-signature PATH File containing input context based
mutational probabilities (signature)
-ef, --elements-file PATH File with the symbols of the elements to
analyze
-e, --elements TEXT Symbol of the element(s) to analyze
-g, --genome [hg38|hg19|mm10|c3h|car|cast|f344]
Genome to use
-emut, --element-mutations INTEGER
Cutoff of element mutations. Default is 2
-cmut, --cluster-mutations INTEGER
Cutoff of cluster mutations. Default is 2
-sw, --smooth-window INTEGER RANGE
Smoothing window. Default is 11
-cw, --cluster-window INTEGER RANGE
Cluster window. Default is 11
-kmer, --kmer [3|5] K-mer nucleotide context
-n, --n-simulations INTEGER number of simulations. Default is 1000
-sim, --simulation-mode [mutation_centered|region_restricted]
Simulation mode
-simw, --simulation-window INTEGER RANGE
Simulation window. Default is 31
-sigcalc, --signature-calculation [frequencies|region_normalized]
Signature calculation: mutation frequencies
(default) or k-mer mutation counts
normalized by k-mer region counts
-siggroup, --signature-group [SIGNATURE|SAMPLE|CANCER_TYPE]
Header of the column to group signatures
calculation
-c, --cores INTEGER RANGE Number of cores to use in the computation.
By default it will use all the available
cores.
--seed INTEGER Seed to use in the simulations
--log-level [debug|info|warning|error|critical]
Verbosity of the logger
--concatenate Calculate clustering on concatenated genomic
regions (e.g., exons in coding sequences)
--clustplot Generate a needle plot with clusters for an
element
--qqplot Generate a quantile-quantile (QQ) plot for a
dataset
--gzip Gzip compress files
-h, --help Show this message and exit.
Copy sample data to the current folder:
[user@cn3335 ~]$ cp -r $ODCLUSTL_DATA/* .Now let's run oncodriveCLUSTL on the sample data. According to the the oncodriveCLUSTL documentation, "The first time that you run OncodriveCLUSTL with a given reference genome, it will download it from our servers. By default the downloaded datasets go to ~/.bgdata. If you want to move these datasets to another folder you have to define the system environment variable BGDATA_LOCAL with an export command."
[user@cn3335 ~]$ oncodriveclustl -i PAAD.tsv.gz -r cds.hg19.regions.gz -o test_output
2023-02-02 08:32:50,073 [110140] INFO root: OncodriveCLUSTL
2023-02-02 08:32:50,073 [110140] INFO root:
input_file: PAAD.tsv.gz
regions_file: cds.hg19.regions.gz
input_signature: None
output_directory: test_output
genome: hg19
element_mutations: 2
cluster_mutations: 2
concatenate: False
smooth_window: 11
cluster_window: 11
k-mer: 3
simulation_mode: mutation_centered
simulation_window: 31
n_simulations: 1000
signature_calculation: frequencies
signature_group: None
cores: 128
gzip: False
seed: None
2023-02-02 08:32:50,075 [110140] INFO root: Initializing OncodriveCLUSTL...
2023-02-02 08:32:50,077 [110140] WARNING root:
Running with default simulating, smoothing and clustering OncodriveCLUSTL parameters. Default parameters may not be optimal for your data.
Please, read Supplementary Methods to perform model selection for your data.
2023-02-02 08:32:50,079 [110140] WARNING root:
Signatures will be calculated as mutation frequencies: # mutated ref>alt k-mer counts / # total substitutions
Please, read Supplementary Methods to perform a more accurate signatures calculation
2023-02-02 08:32:50,080 [110140] INFO root: Parsing genomic regions and mutations...
2023-02-02 08:33:01,448 [110140] INFO root: Regions parsed
2023-02-02 08:33:01,639 [110140] INFO root: Mutations parsed
2023-02-02 08:33:01,714 [110140] INFO root: Validated elements in genomic regions: 20169
2023-02-02 08:33:01,715 [110140] INFO root: Validated elements with mutations: 5183
2023-02-02 08:33:01,716 [110140] INFO root: Total substitution mutations: 7913
2023-02-02 08:33:01,717 [110140] INFO root: Computing signature...
2023-02-02 08:33:05,327 [110140] INFO root: Signature computed
2023-02-02 08:33:05,349 [110140] INFO root: Calculating results 1456 elements...
2023-02-02 08:33:05,352 [110140] INFO root: Iteration 1 of 15
simulations: 100%|█████████████████████████████████| 3/3 [00:14<00:00, 4.84s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:36<00:25, 1.04it/s]
2023-02-02 08:34:59,477 [110140] INFO root: Iteration 2 of 15
simulations: 100%|█████████████████████████████████| 7/7 [00:13<00:00, 1.95s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:30<00:24, 1.11it/s]
2023-02-02 08:36:45,989 [110140] INFO root: Iteration 3 of 15
simulations: 100%|█████████████████████████████████| 5/5 [00:22<00:00, 4.46s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:17<00:20, 1.30it/s]
2023-02-02 08:38:29,579 [110140] INFO root: Iteration 4 of 15
simulations: 100%|█████████████████████████████████| 5/5 [00:18<00:00, 3.70s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:34<00:25, 1.07it/s]
2023-02-02 08:40:25,999 [110140] INFO root: Iteration 5 of 15
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post processing: 79%|██████████████████████▉ | 101/128 [01:38<00:26, 1.02it/s]
2023-02-02 08:42:39,555 [110140] INFO root: Iteration 6 of 15
simulations: 100%|███████████████████████████████| 12/12 [00:30<00:00, 2.54s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:16<00:20, 1.32it/s]
2023-02-02 08:44:30,511 [110140] INFO root: Iteration 7 of 15
simulations: 100%|█████████████████████████████████| 7/7 [00:15<00:00, 2.23s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:25<00:22, 1.19it/s]
2023-02-02 08:46:15,403 [110140] INFO root: Iteration 8 of 15
simulations: 100%|███████████████████████████████| 11/11 [00:17<00:00, 1.59s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:29<00:23, 1.13it/s]
2023-02-02 08:48:07,030 [110140] INFO root: Iteration 9 of 15
simulations: 100%|███████████████████████████████| 13/13 [00:51<00:00, 3.95s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:34<00:25, 1.07it/s]
2023-02-02 08:50:36,900 [110140] INFO root: Iteration 10 of 15
simulations: 100%|█████████████████████████████████| 9/9 [00:13<00:00, 1.53s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:41<00:27, 1.00s/it]
2023-02-02 08:52:35,327 [110140] INFO root: Iteration 11 of 15
simulations: 100%|█████████████████████████████████| 5/5 [00:14<00:00, 2.96s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:28<00:23, 1.14it/s]
2023-02-02 08:54:22,365 [110140] INFO root: Iteration 12 of 15
simulations: 100%|███████████████████████████████| 10/10 [00:20<00:00, 2.09s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:37<00:25, 1.04it/s]
2023-02-02 08:56:24,457 [110140] INFO root: Iteration 13 of 15
simulations: 100%|█████████████████████████████████| 7/7 [00:38<00:00, 5.56s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:28<00:23, 1.14it/s]
2023-02-02 08:58:35,490 [110140] INFO root: Iteration 14 of 15
simulations: 100%|███████████████████████████████| 10/10 [00:18<00:00, 1.85s/it]
post processing: 79%|██████████████████████▉ | 101/128 [01:33<00:24, 1.09it/s]
2023-02-02 09:00:31,237 [110140] INFO root: Iteration 15 of 15
simulations: 100%|█████████████████████████████████| 1/1 [00:05<00:00, 5.99s/it]
post processing: 45%|█████████████▎ | 57/128 [00:56<01:10, 1.01it/s]
2023-02-02 09:01:40,325 [110140] INFO root: Elements results calculated
2023-02-02 09:01:40,381 [110140] INFO root: Clusters results calculated
2023-02-02 09:01:40,383 [110140] INFO root: Finished