Infer tree sequences from genetic variation data.
Project description
tsinfer ![](https://pypi-camo.freetls.fastly.net/be77a570dd7d6fd0407f412c38a52b081f1bcc18/68747470733a2f2f7261772e67697468756275736572636f6e74656e742e636f6d2f74736b69742d6465762f7473696e6665722f6d61696e2f646f63732f7473696e6665725f6c6f676f2e737667)
Infer a tree sequence from genetic variation data
The documentation contains details of how to use this software, including installation instructions.
The initial algorithm, its rationale, and results from testing on simulated and real data are described in the following Nature Genetics paper:
Jerome Kelleher, Yan Wong, Anthony W Wohns, Chaimaa Fadil, Patrick K Albers and Gil McVean (2019) Inferring whole-genome histories in large population datasets. Nature Genetics 51: 1330-1338
Tsinfer versions 0.2.0 onwards allow missing data and provide a fully parameterised Li & Stephens matching algorithm (i.e. which allows mismatch). These improvements are described in the following Science paper:
Anthony Wilder Wohns, Yan Wong, Ben Jeffery, Ali Akbari, Swapan Mallick, Ron Pinhasi, Nick Patterson, David Reich, Jerome Kelleher, and Gil McVean (2022) A unified genealogy of modern and ancient genomes. Science 375: eabi8264
Please cite either or both of these if you use tsinfer
in your work. Code to reproduce the results in the first paper is present in a separate GitHub repository.
Note that tsinfer
does not attempt to infer node times (i.e. branch lengths of the
inferred trees). If you require a tree sequence where the dates of common ancestors
are expressed in calendar or generation times, you should post-process the tsinfer
output using software such as tsdate
.
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