https://github.com/stjudecloud/mtsg
Find and quantify COSMIC mutational signatures across samples
https://github.com/stjudecloud/mtsg
Last synced: 11 months ago
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Find and quantify COSMIC mutational signatures across samples
- Host: GitHub
- URL: https://github.com/stjudecloud/mtsg
- Owner: stjudecloud
- License: mit
- Created: 2018-08-06T21:15:03.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2023-07-06T20:15:47.000Z (almost 3 years ago)
- Last Synced: 2025-01-22T05:28:48.953Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 478 KB
- Stars: 2
- Watchers: 4
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# Mutational Signatures
**Mutational Signatures** (abbreviated as **mtsg**) finds and quantifies [COSMIC
mutational signatures] across samples.
mtsg uses a base set of mutational signatures extracted by [SigProfiler] for
[single-base substitutions] (SBS), i.e., single-nucleotide variants (SNV),
using 2780 whole-genome variant calls from the ICGC/TCGA [Pan-Cancer Analysis
of Whole Genomes] (PCAWG) project.
[COSMIC mutational signatures]: https://cancer.sanger.ac.uk/cosmic/signatures
[SigProfiler]: https://cancer.sanger.ac.uk/cosmic/signatures/sigprofiler.tt
[single-base substitutions]: https://cancer.sanger.ac.uk/cosmic/signatures/SBS/index.tt
[Pan-Cancer Analysis of Whole Genomes]: https://dcc.icgc.org/pcawg
## Prerequisites
* [Python] ^3.8
* [sigproSS] ^0.0.0
[Python]: https://www.python.org/
[sigproSS]: https://github.com/AlexandrovLab/SigProfilerSingleSample
## Install
Use [Poetry] to install mtsg and its dependencies.
```
$ poetry install --no-dev
```
`mtsg init` can then be used to install base mutational matrices given a
supported genome build.
```
$ mtsg init --genome-build
```
Replace `` with one of `GRCh37`, `GRCh38` (Homo sapiens),
`mm9`, `mm10` (Mus musculus), or `rn6` (Rattus norvegicus).
[Poetry]: http://python-poetry.org/
## Usage
Mutational Signatures is installed as the executable `mtsg`. It has three
commands: `init`, `run`, and `visualize`.
### Run
`run` is used to profile samples (as VCFs) using known mutational signatures.
The selected genome build must match the input VCFs and previously installed
during the installation.
```
usage: mtsg run [-h] [--dst-prefix DST_PREFIX] [--genome-build {GRCh37,GRCh38,mm9,mm10,rn6}] src-prefix
positional arguments:
src-prefix
optional arguments:
-h, --help show this help message and exit
--dst-prefix DST_PREFIX
--genome-build {GRCh37,GRCh38,mm9,mm10,rn6}
```
### Visualize
`visualize` uses signature activities (generated by `run` and typically named
`Sig_activities.txt`) to create an interactive plot.
```
usage: mtsg visualize [-h] --reference REFERENCE --output OUTPUT src
positional arguments:
src
optional arguments:
-h, --help show this help message and exit
--reference REFERENCE
--output OUTPUT
```
## Docker
Mutational Signatures has a `Dockerfile` to create a container image, which
sets up and installs the required runtime and dependencies. It installs
reference files for only GRCh38 and uses COMSIC mutational signatures 3.1. To
build and use this image, [install Docker](https://docs.docker.com/install)
for your platform.
### Build
In the Mutational Signatures project directory, build the container image.
```
$ docker image build --tag mtsg .
```
### Run
The image uses `mtsg` as its entrypoint, giving access to all commands.
```
$ docker container run mtsg
```
For example, a typical workflow is to run the `run` command followed by `visualize`.
```
$ docker container run \
--rm \
--mount type=bind,source=$PWD/data,target=/data \
--mount type=bind,source=$PWD/results,target=/results \
mtsg \
run \
--dst-prefix /results \
/data
$ docker container run \
--rm \
--mount type=bind,source=$PWD/references,target=/references,readonly \
--mount type=bind,source=$PWD/results,target=/results \
mtsg \
visualize \
--reference /references/reference.tsv \
--output /results/signatures.html \
/results/Sig_activities.txt
```
## References
* Alexandrov, L.B., Kim, J., Haradhvala, N.J. _et al_. The repertoire of
mutational signatures in human cancer. _Nature_ **578**, 94–101 (2020).
https://doi.org/10.1038/s41586-020-1943-3
* Bergstrom, E.N., Huang, M.N., Mahto, U. _et al_.
SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns
of small mutational events. _BMC Genomics_ **20**, 685 (2019).
https://doi.org/10.1186/s12864-019-6041-2