Skip to main content

Computes Tajimas D, the Pi- or Watterson-Estimator for multiple sequences.

Project description

tajimas_d logo

Compute the Tajima's-D, Pi-Estimator or Watterson-Estimator for multiple sequences.

This module is now part of the bfx suite. See https://py-bfx.readthedocs.io for more information.

Test Badge Python Version Badge Download Badge Code style: black

Tajima's D is a population genetic test statistic that computes the difference between the mean number of pairwise differences and the number of segregating sites. It is used to determine whether a population is expanding or shrinking.

Tajima's D

Tajima's D is defined as follows: $\theta_\text{Tajima}=\frac{\theta_{\pi}%20-%20\theta_{W}}{\sqrt{\text{Var}(\theta_{\pi}-\theta_{W})}}$

If $\theta_\text{Tajima}<0$, there are many rare variants, indicating an expanding population.

Whereas $0<\theta_\text{Tajima}$, indicates an declining population as there are many intermediate variants.

A result is consideres significant if $\theta_\text{Tajima}<-2$ or $2<\theta_\text{Tajima}$.

Pi-Estimator

The π estimator is the average number of pairwise differences between any two sequences:

$\theta_{\pi}=\frac{\text{Nr. of pairwise differences}}{\binom{n}{2}}$

Watterson-Estimator

The Watterson estimator is the expected number of segregating sites.

$\theta_{W}=\frac{\text{Nr. of segregating sites}}{\Sigma_{i=1}^{n-1}\frac{1}{i}}$

Installation

Using pip / pip3:

pip install tajimas_d

Using conda:

conda install -c bioconda tajimas_d

Or by source:

git clone git@github.com:not-a-feature/tajimas_d.git
cd tajimas_d
pip install .

How to use

from tajimas_d import tajimas_d, watterson_estimator, pi_estimator

sequences = ["AAAA", "AAAT", "AAGT", "AAGT"]

theta_tajima = tajimas_d(sequences)
theta_pi = pi_estimator(sequences)
theta_w = watterson_estimator(sequences)

Standalone version

The standalone version requires miniFasta>=2.2 to be installed.

usage: tajimas_d [-h] -f PATH [-p] [-t] [-w]

tajimas_d: Compute Tajima's D, the Pi- or Watterson-Estimator for multiple
sequences.

optional arguments:
  -h, --help            show this help message and exit
  -f PATH, --file PATH  Path to fasta file with all sequences.
  -p, --pi              Compute the Pi-Estimator score.
  -t, --tajima          Compute the Pi-Estimator score. (default)
  -w, --watterson       Compute the Watterson-Estimator score.

License

Copyright (C) 2024 by Jules Kreuer - @not_a_feature

This piece of software is published unter the GNU General Public License v3.0 TLDR:

Permissions Conditions Limitations
✓ Commercial use Disclose source ✕ Liability
✓ Distribution License and copyright notice ✕ Warranty
✓ Modification Same license
✓ Patent use State changes
✓ Private use

Go to LICENSE.md to see the full version.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tajimas_d-2.0.4.tar.gz (18.5 kB view details)

Uploaded Source

Built Distribution

tajimas_d-2.0.4-py3-none-any.whl (18.1 kB view details)

Uploaded Python 3

File details

Details for the file tajimas_d-2.0.4.tar.gz.

File metadata

  • Download URL: tajimas_d-2.0.4.tar.gz
  • Upload date:
  • Size: 18.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.22

File hashes

Hashes for tajimas_d-2.0.4.tar.gz
Algorithm Hash digest
SHA256 13c9f71e900649ea459cceb354581e314d548ee0205f5f3df465b100a29da4b8
MD5 43520bf46854e9b05f5c551624bad278
BLAKE2b-256 abea07b9c07910208e4e4db434b398c8a7d814384250aa9fb5c90e7bcd9dd11e

See more details on using hashes here.

File details

Details for the file tajimas_d-2.0.4-py3-none-any.whl.

File metadata

  • Download URL: tajimas_d-2.0.4-py3-none-any.whl
  • Upload date:
  • Size: 18.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.22

File hashes

Hashes for tajimas_d-2.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 3af5054717d85827171b4190406891700767adfc3a877ae30227afa3f8288dae
MD5 1a2b75419f3ae5933a3adfdb2d262c13
BLAKE2b-256 dba1abab6365172e314f5cae623bc4adf06de9d2f247b8505b6577e71216fdc6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page