asmc-asmc 1.2

ASMC is a method to efficiently estimate pairwise coalescence time along the genome

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:

pip install asmc-asmc

Documentation

The following pages of documentation contains specific information:

• Quickstart guide for users
• ASMC python docs
• FastSMC python docs

This Python module is currently available on Linux and macOS.

Example Jupyter notebooks showcasing basic functionality can be found here:

• Example 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

v1.2 (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.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. 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)

Legacy repository

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

First public release of FastSMC, with functionality as described and used in this paper.