ASMC is a method to efficiently estimate pairwise coalescence time along the genome
Project description
ASMC and FastSMC
This repository provides ASMC and its extension FastSMC, implemented in C++ with Python bindings. Prebuilt CPython wheels are available for Linux (compatible with glibc ≥ 2.28) and macOS (built on macOS 15 for x86_64 and macOS 14 for arm64).
| Platform \ CPython | ≤3.8 | 3.9 | 3.10 | 3.11 | 3.12 | 3.13 | 3.14 |
|---|---|---|---|---|---|---|---|
| Linux x86_64 | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Linux aarch64 | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| macOS Intel (x86_64) | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| macOS Apple Silicon (arm64) | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Quickstart
Install the Python module from PyPI
Most functionality is available through a Python module which can be installed with:
pip install asmc-asmc
Documentation
The following pages of documentation contains specific information:
This Python module is currently available on Linux and macOS.
Example Jupyter notebooks showcasing basic functionality can be found here:
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
v1.4.0 (2025-10-22)
Breaking changes
- Dependencies are no longer managed with vcpkg. Boost and zlib should now be obtained from a system package manager, while other dependencies are fetched using CMake's FetchContent during configuration.
Other changes
-
Added support for cross-platform SIMD vectorization using the Google Highway library. This improves performance by dynamically dispatching to the most powerful supported instruction set at runtime (e.g., AVX-512, AVX2, or NEON), ensuring optimal performance on different CPU architectures.
-
Python wheels are now available for Linux and macOS on both x86_64 and arm64/AArch64 architectures, for CPython versions 3.9 to 3.14 inclusive.
v1.3.1 (2023-06-30)
Breaking changes
None
Other changes
- The location of a
.mapor.map.gzfile can now be optionally specified explicitly: previously it was assumed to be at theinFileRoot.
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_inparameter 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).
Breaking changes
- Fixed an issue with demographic models.
The
CEU.demodemographic 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. 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 for details.
- New, more extensive, documentation is available.
v1.1 (2021-01-20)
Improvements to documentation and default use. No changes to any core functionality.
Breaking changes
- The hashing functionality, previously named
GERMLINE, has been renamed tohashing. This includes the command line flag for turning this behaviour on/off, which is now--hashing.
Other changes
--hashingis now ON by default when running the FastSMC executable: previously,--GERMLINEwas 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.shthat 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)
First public release of FastSMC, with functionality as described and used in this paper.
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