Welcome to the project page for MetaSIPSim. This is a tool for simulating metagenomic stable isotope probing (metagenomic-SIP) datasets, including next-generation read libraries. Metagenomic-SIP allows us to link microbial genomes to function within an environmental sample. Metagenomic-SIP improves our ability to recover, assemble, and bin genomes from target, isotopically labeled microbes, compared to conventional shotgun metagenomics.
MetaSIPSim can be used to simulate read libraries for use in testing experimental parameters and in the development of analytical tools for metagenomic-SIP methodologies. This can save on costs and time where preliminary experiments or in vitro mock communities would otherwise be used.
MetaSIPSim can be run using linux or unix based operating systems and has been successfully and fully tested using an Ubuntu version 16.04.4 system as well as macOSX version 10.12.6. MetaSIPSim is currently incompatible with windows.
MetaSIPSim runs with python 2.7 and is currently incompatible with python 3.6. For those familiar with it, we highly recommend using anaconda environments for version control and installing the dependencies.
To run MetaSIPSim scripts you must install the following python modules. All are available through conda.
- numpy (≥ 1.16.3)
- pandas (≥ 0.24.2)
- Bioptyhon (≥ 1.73)
- scipy (≥ 1.2.1)
- pyfasta (≥ 0.5.2)
If you want to use the included script for converting fasta files to fastq format, you also need to install
- InSilicoSeq (≥ 1.3.6)
To install MetaSIPSim, simply clone this repo. You can then call the MetaSIPSim scripts directly from the cloned directory.
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SIPSim_metagenome.py: This script simulates metagenomic-SIP datasets based on input experimental parameters and a simulated community. Output from this script can be a table of DNA fragments with their abundances in a given gradient window, a table of next-gen sequencing reads recovered in a gradient window, or these recovered reads in fasta format.
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nonSIP_metagenome.py: This script simulates conventional shotgun metagenomic datasets. This can be used to compare metagenomic-SIP methodologies to conventional metagenomics. Input can the identical to that of SIPSim_metagenome.py. Output from this script can be a table of DNA fragments with their abundances in a given gradient window, a table of next-gen sequencing reads recovered in a gradient window, or these recovered reads in fasta format.
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fasta2fastq.py: This script converts fasta formatted read libraries generated by SIPSim_metagenome.py and nonSIP_metagenome.py into fastq format with sequencing errors and quality scores. This script relies heavily on InSilicoSeq functions. Error models used for this function can be taken from the InSilicoSeq package, generated by the user with InSilicoSeq, or the ones provided here (copies of the ones from a local InSilicoSeq build).
For both SIPSim_metagenome.py and nonSIP_metagenome.py, input is a configuration file containing paths to input files or directories, experimental parameters including gradient variables, and sequencing variables. For a more thorough description of the configuration file, please see the manual. This same configuration file can be used for both simulations however the gradient parameters are not used for nonSIP_metagenome.py
Once the configuration file is generated, you can run these scripts by running:
python PATH_TO_MetaSIPSim/bin/SIPSim_metagenome.py CONFIG_FILE
python PATH_TO_MetaSIPSim/bin/nonSIP_metagenome.py CONFIG_FILE
To convert the simulated read library in fasta to fastq format, simply run:
python PATH_TO_MetaSIPSim/bin/fasta2fastq.py i d e l t p
This script requires the following inputs:
- i: The input fasta file.
- d: Indicates whether the input file contains [forward] or [reverse] reads.
- e: The error model file, which can be generated with InSilicoSeq or one of the ones provided.
- l: The length of a read in bp.
- t: The path to a temporary directory to store intermediate files in.
- p: The number of processors to use.
For a basic example of using MetaSIPSim, check out:
- example_simulation.ipynb: A simple example for simulating metagenomic-SIP libraries as well as conventional shotgun libraries.
- example_parameters.cfg: An example configuration file. For more info on each parameter included, check out the manual.
For more in depth examples you can also check out:
- Validation: The notebooks for running the validation of MetaSIPSim against empirical data. These are also fairly simple yet show a good example for using MetaSIPSim with real experimental parameters.
- Case study: The notebooks for running the case study simulations used in the paper (LINK). These are complex examples using simulated bacterial communities.
Barnett, S.E., Buckley, D.H. Simulating metagenomic stable isotope probing datasets with MetaSIPSim. BMC Bioinformatics 21, 37 (2020). https://doi.org/10.1186/s12859-020-3372-6
- 1.0.1: Fixed issue where NaN abundances produced due to very short fragments were preventing read generation. See line 573 in SIPSim_metagenome.py and line 400 in nonSIP_metagenome.py.
- 1.0.0: Published version with new citation and fixed progress output for non-SIP metagenome simulation.
- 0.1.0: Initial commit of development version.
Many thanks to Nicholas Youngblut, the author of the original SIPSim toolkit, for advice and mentorship during development of this tool. Some of the functions, particularly those involved in dealing with fragment buoyant densities, are derived or taken from SIPSim.
For more information on SIPSim, please refer to:
Youngblut ND, Barnett SE, Buckley DH. SIPSim: A Modeling Toolkit to Predict Accuracy and Aid Design of DNA-SIP Experiments. Frontiers in Microbiology 2018;9:570. doi: 10.3389/fmicb.2018.00570
or the project site https://github.com/nick-youngblut/SIPSim.
The script for converting read library files from fasta to fastq format relies heavily on code from InSilicoSeq. For more information on this program please refer to:
Gourlé H, Karlsson-Lindsjö O, Hayer J, Bongcam-Rudloff E. Simulating Illumina data with InSilicoSeq. Bioinformatics 2018;35(3):521-522. doi: 10.1093/bioinformatics/bty630
MetaSIPSim is under an MIT license. For more information read LICENSE.