Skip to main content

TruSD co-infers selection coefficients and genetic drift from allele trajectories using a maximum-likelihood framework.

Project description

TruSD

Trajectories under Selection and Drift is an implementation of a method that co-infers selection coefficients and genetic drift from allele trajectories using a maximum-likelihood framework.

If you find the software useful in your research please cite this package.

Installation

TruSD needs Python 3.6 or newer. Python 2 is not supported! TruSD was only tested on Linux (Ubuntu), but should work on Mac and Windows as well.

We suggest to use a virtual environment for use of TruSD. To install TruSD, run:

pip3 install trusd  # add --user to install only for the user

This will install TruSD as importable module and three command line tools, trusd, trusd-plot, and trusd-sim.

Update

If you later want to update TruSD, use the pip command:

pip3 install --upgrade trusd

Running TruSD from within a Python script

Import the trusd module from your Python 3 script:

# inside python3 script or interactive prompt
import trusd
help(trusd.trusd) # gives package content

For an example, download two files (for example with wget):

wget https://github.com/mathiasbockwoldt/TruSD/blob/master/examples/min_working_example.py
wget https://github.com/mathiasbockwoldt/TruSD/blob/master/examples/traj_example.txt

You can start an example run with

python3 min_working_example.py

The min_working_example.py is documented to explain the basic steps. It uses traj_example.txt as input and produces outfile.txt (the results), outfile.json (the metadata) and outfile.pdf (the plot).

Running TruSD as command line program

The command line programs are self-explanatory using the --help flag.

trusd --help
trusd-plot --help
trusd-sim --help

The parameters are the same as in the Python modules.

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

TruSD-0.0.6.tar.gz (13.2 kB view details)

Uploaded Source

Built Distribution

TruSD-0.0.6-py3-none-any.whl (15.9 kB view details)

Uploaded Python 3

File details

Details for the file TruSD-0.0.6.tar.gz.

File metadata

  • Download URL: TruSD-0.0.6.tar.gz
  • Upload date:
  • Size: 13.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.8.10

File hashes

Hashes for TruSD-0.0.6.tar.gz
Algorithm Hash digest
SHA256 c820116cb5d0515dfa9bc8367255bc0424a70be358b4542c400e79813f13e08f
MD5 008e0bf85c699f16ea8caae46dbef6c8
BLAKE2b-256 e5b2f646673549d29d34dbaf43190160e0d8a21e3cb1995e21ebe3686930d216

See more details on using hashes here.

File details

Details for the file TruSD-0.0.6-py3-none-any.whl.

File metadata

  • Download URL: TruSD-0.0.6-py3-none-any.whl
  • Upload date:
  • Size: 15.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.8.10

File hashes

Hashes for TruSD-0.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 345a7e93deb9ea00a06e848171ab9f52e913b0cf573b8ad954606e562081a02f
MD5 7bb70e3333661a9f08856903886f0dc2
BLAKE2b-256 558ca276d5b63b8b171243f900557e9a9aa474b252da3dd093a4fa4240d85061

See more details on using hashes here.

Supported by

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