ecSimulator simulates ecDNA genome structures with user-specifiable parameters for SV frequencies, size, and mechanism of origin. Users can invoke a read simulator on the simulated structures to generate simulated sequencing data.
It takes as input a reference genome fasta and a yaml configuration file.
The latest version of ecSimulator is 0.6.0.
ecSimulator requires python3 and the numpy
and intervaltree
python libraries.
pip3 install numpy intervaltree # or conda install intervaltree, etc.
git clone https://github.com/jluebeck/ecSimulator.git
ecSimulator also requires the AmpliconArchitect data repo to be present, which contains reference genome builds and genome annotations.
- Download AA data repositories and set environment variable AA_DATA_REPO:
- Go here to locate data repo(s) of your choice and make note of the URL you want.
- Wget and set a bash environment variable AA_DATA_REPO to point to the data_repo directory:
mkdir data_repo && cd data_repo wget [url of reference_build] tar zxf [reference_build].tar.gz # command below exports a bash variable which is the parent directory of the individual data repos echo export AA_DATA_REPO=$PWD/ >> ~/.bashrc touch coverage.stats && chmod a+rw coverage.stats source ~/.bashrc
A reference genome fasta file from which to extract genome sequences is also required. These are available in the AmpliconArchitect data repo for users who may already have that tool installed.
ecSimulator allows users to simulate nanopore reads from the resulting structures, using NanoSim. Nanosim can be installed by performing
conda install -c bioconda nanosim
We provide a pre-generated NanoSim read simulation model generated using input data from a Promethion with version 10.4.1 flow cell and Guppy as the basecaller (version [email protected]). No additional configuration of the simulator is required by the user.
The memory an CPU requirements of ecSimulator are minimal, but please try to have more than 4Gb RAM available. The simulator should finish within 30s-1min for typical simulation runs. Simulating thousands of structures may take slightly longer.
An example command to generate an ecDNA of episomal origin with at least two non-overlapping genomic segments with default SV frequencies:
ecSimulator/src/ecSimulator.py --ref_name GRCh38 --ref_fasta /path/to/hg38.fa -o test
Or with customized simulation parameters:
ecSimulator/src/ecSimulator.py --ref_name GRCh38 --ref_fasta /path/to/hg38.fa --config_file your_config.yaml -o test
To simulate Nanopore reads from the simulated focal amplification (using NanoSim), you can do the following
ecSimulator/src/run_nanosim.py -o test_amplicon_1_read_sim --amplicon_fasta test_amplicon1.fasta --amplicon_coverage 1
ecSimulator takes the following command-line arguments:
Command | Default | Description |
---|---|---|
--ref_name |
(Required) One of [hg19, GRCh37, GRCh38, mm10 ] |
|
--ref_fasta |
(Required) Path to the reference genome fasta file. In most cases this may just be the fasta in the AA data repo. | |
--config_file |
default_config.yaml |
(Optional) Path to ecSimulator run configuration yaml file. Defaults to the default_config.yaml file in the ecSimulator/src/ directory. |
-o\--output_prefix |
(Required) A prefix for the output files (e.g. my_results_dir/sim_name ) |
|
-n\--num_amplicons |
1 | (Optional) The number of amplicons to simulate with the settings given by the config file. |
-v\--version |
(Optional) Print the version number and exit. |
The ecDNA structure simulations performed by ecSimulator can be customized a number of ways. A default version is provided in
src/default_config.yaml
and will be used unless a different file is given for --config_file
. The run configuration YAML file supports the following customizations:
random_seed: 0 # sets a seed for the simulator, set to 'None' for random seed.
target_size: 2000000 # target size for the ecDNA size, in basepairs. Target size is approximate due to duplications and deletions.
origin: "episome" # can be either episome, chromothripsis, or two-foldback.
mean_segment_size: 150000 # refers to the average distance between breakpoints.
min_segment_size: 1000 # minimum segment length allowed between breakpoints
num_breakpoints: "auto" # number of breakpoints to assign inside the amplicon (approximate). Does not count initial breakpoints to form & circularize interval
num_intervals: 2 # number of non-overlapping genomic regions to use for the amplicon. Breakpoints will be assigned within these larger intervals. Recommend setting to "auto" if origin is not "episome".
same_chromosome: False # Allow intervals to be sampled from multiple different chromosomes (if num_intervals > 1).
allow_interval_reuse: True # allow different amplicons from the run to re-use some of the same genomic coordinates.
overlap_bed: "" # specify a path to a bed file of regions the amplicon must overlap.
viral_insertion: False # create a hybrid human-viral ecDNA
viral_strain: "hpv16.fasta" # Only used if viral_insertion is 'True'. Specify the name of the viral strain to be used from the oncoviruses directory.
sv_probs: # probability this type of SV occurs during the iterative rearrangement process. Not mutually exclusive events.
del: 0.6
dup: 0.5
inv: 0.4
trans: 0.4 # translocation (moves segment to random location inside amplicon)
fback: 0.05 # foldback, this stacks on top of the probability of independently getting both a dup and inv at the same time.
ecSimulator is designed to keep ecDNA from getting approximately 20% larger or smaller than the target size, so the actual duplication and deletion probabilities in the simulated ecDNA may be lower than specified by user.
- Fasta file encoding the simulated ecDNA structure.
- AmpliconArchitect-formatted
_cycles.txt
file, encoding the order and orientation of the genomic segments. - AmpliconArchitect-formatted
_graph.txt
file, encoding the genomic segments and SVs (breakpoint graph).
Coordinates reported in the output files are based.
ecSimulator will also create a directory of the intermediate structures from the simulation, containing the same files as described above for the final amplicon, but also for each intermediate structure created during the simulation. This can be useful if you later want to create mixtures of heterogeneous but highly similar amplicons.
Users can use the cycles_file_to_fasta.py
script to convert any intermediate (or generally, any) AA-formatted _cycles.txt
file to a fasta.
The Nanosim process will create two fastq files (aligned.fastq and unaligned.fastq) and a file describing the locations of the errors in the reads. A complete description of these files is available here.
To combine the background and amplicon fastq files, users an simply do
cat [sample]_amplicon_unaligned_reads.fastq [sample]_amplicon_aligned_reads.fastq [sample]_background_unaligned_reads.fastq [sample]_background_aligned_reads.fastq