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asmc-asmc-1.3
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مشاهده بیشترتوضیحات
ASMC is a method to efficiently estimate pairwise coalescence time along the genome
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | asmc-asmc-1.3 |
| نام | asmc-asmc |
| نسخه کتابخانه | 1.3 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | PalamaraLab (https://palamaralab.github.io/) |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://github.com/PalamaraLab/ASMC/ |
| آدرس اینترنتی | https://pypi.org/project/asmc-asmc/ |
| مجوز | - |
[](https://github.com/PalamaraLab/ASMC/actions/workflows/ubuntu-unit.yml)
[](https://github.com/PalamaraLab/ASMC/actions/workflows/macos-unit.yml)
[](https://github.com/PalamaraLab/ASMC/actions/workflows/ubuntu-python.yml)
[](https://github.com/PalamaraLab/ASMC/actions)
[](https://github.com/PalamaraLab/ASMC/actions)
[](https://github.com/PalamaraLab/ASMC/actions)
[](https://codecov.io/gh/PalamaraLab/ASMC)
# ASMC and FastSMC
This repository contains ASMC and an extension, FastSMC, together with python bindings for both.
## Quickstart
### Install the Python module from PyPI
Most functionality is available through a Python module which can be installed with:
```bash
pip install asmc-asmc
```
### Documentation
The following pages of documentation contains specific information:
- [Quickstart guide for users](https://github.com/PalamaraLab/ASMC/blob/main/docs/quickstart_user.md)
- [ASMC python docs](https://github.com/PalamaraLab/ASMC/blob/main/docs/asmc_python.md)
- [FastSMC python docs](https://github.com/PalamaraLab/ASMC/blob/main/docs/fastsmc_python.md)
This Python module is currently available on Linux and macOS.
Example Jupyter notebooks showcasing basic functionality can be found here:
- [Example notebooks](https://github.com/PalamaraLab/ASMC/tree/main/notebooks)
## License
ASMC and FastSMC are distributed under the GNU General Public License v3.0 (GPLv3). For any questions or comments on ASMC, please contact Pier Palamara using `<lastname>@stats.ox.ac.uk`.
## Reference
If you use this software, please cite the appropriate reference(s) below.
The ASMC algorithm and software were developed in
- P. Palamara, J. Terhorst, Y. Song, A. Price. High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability. *Nature Genetics*, 2018.
The FastSMC algorithm and software were developed in
- J. Nait Saada, G. Kalantzis, D. Shyr, F. Cooper, M. Robinson, A. Gusev, P. F. Palamara. Identity-by-descent detection across 487,409 British samples reveals fine-scale evolutionary history and trait associations. *Nature Communications*, 2020.
# ASMC Release Notes
## v1.3 (2023-03-03)
### Breaking changes
None
### Other changes
- Decoding a batch can now be done in a selected subregion with from / to indices.
A `cm_burn_in` parameter takes into account additional variants on either side of the subregion for HMM burn-in.
- Allow the user to access selected attributes of the DecodingParams and Data from the ASMC object.
- Python continuous integration now uses Python 3.8 and 3.11 (previously 3.6 and 3.9)
- Update Catch to v2.13.
## v1.2 (2021-09-28)
All functionality for ASMC and FastSMC is now in this repository ([link](https://github.com/PalamaraLab/ASMC)).
### Breaking changes
- Fixed an issue with demographic models.
The `CEU.demo` demographic model and the decoding quantities for CEU+UKBB previously provided in the repository were mistakenly encoded as diploid rather than haploid.
CEU.demo and CEU+UKBB decoding quantities have now been updated and can be found in [this repository](https://github.com/PalamaraLab/ASMC_data).
Also see the manual for a note on how this affects analyses.
### Other changes
- New API for decoding pairs with ASMC.
In addition to running full analyses as described in the ASMC paper, users can now decode specific pairs and get back a variety of summary statistics.
See the [ASMC python documentation](https://github.com/PalamaraLab/ASMC/blob/main/docs/asmc_python.md) for details.
- New, more extensive, [documentation](https://github.com/PalamaraLab/ASMC/blob/main/docs/) is available.
## v1.1 (2021-01-20)
[Legacy repository](https://github.com/PalamaraLab/FastSMC/releases/tag/v1.1)
Improvements to documentation and default use.
No changes to any core functionality.
### Breaking changes
- The hashing functionality, previously named `GERMLINE`, has been renamed to `hashing`.
This includes the command line flag for turning this behaviour on/off, which is now `--hashing`.
### Other changes
- `--hashing` is now ON by default when running the FastSMC executable: previously, `--GERMLINE` was OFF by default.
- Extra output, including the IBD segment length, posterior mean, and MAP, are now on by default.
This behaviour can be toggled with the flags `--segmentLength`, `--perPairPosteriorMeans`, `--perPairMAP`.
- An example script has been added to `cpp_example/FastSMC_example_multiple_jobs.sh` that demonstrates how to run FastSMC with multiple jobs simultaneously.
- The README has been updated to focus on FastSMC functionality.
- More robust checking is now used to verify the decoding quantities file is correct before reading it.
- CMake will now, by default, build in Release mode (giving 03 optimisation on Linux).
Previously, Debug was used by default.
## v1.0 (2020-09-18)
[Legacy repository](https://github.com/PalamaraLab/FastSMC/releases/tag/v1.0)
First public release of FastSMC, with functionality as described and used in [this paper](https://doi.org/10.1038/s41467-020-19588-x).
نیازمندی
| مقدار | نام |
|---|---|
| - | jupyter |
| - | numpy |
| - | pandas |
| - | asmc-preparedecoding |
| - | matplotlib |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl asmc-asmc-1.3:
pip install asmc-asmc-1.3.whl
نصب پکیج tar.gz asmc-asmc-1.3:
pip install asmc-asmc-1.3.tar.gz