iTRAILS Documentation¶
Welcome to the iTRAILS documentation landing page. iTRAILS is a command-line tool designed to infer population parameters and reconstruct evolutionary histories from genomic data using a coalescent hidden Markov model framework. This landing page provides a quick start with installation instructions and an overview of basic usage. Detailed guides for each CLI function are available on their own dedicated pages.
Overview¶
iTRAILS builds upon the original TRAILS framework [1] by offering a more programmatic and user-friendly implementation for:
Parameter Optimization: Estimate key population parameters by maximizing the likelihood of genomic alignment data.
Gene Tree Decoding: Use both Viterbi and posterior decoding to determine the most likely sequence of hidden states (gene tree topologies) across genomic segments.
Installation¶
iTRAILS is available both on PyPi and via conda. Choose the installation method that best fits your environment.
Using PyPi
pip install itrails
Using conda
conda install conda-forge::itrails
Basic Usage¶
iTRAILS consists of several command-line functions. Here’s a brief overview of the core functionalities:
itrails-optimize: Optimizes critical population parameters using a YAML configuration file along with input genomic data. _Example usage:_
itrails-optimize config.yaml --input path/to/alignment.maf --output path/to/output_prefix
itrails-viterbi: Applies Viterbi decoding to infer the most likely sequence of gene tree topologies along the genome.
itrails-posterior: Computes the posterior probability distribution of hidden states at every alignment position.
Note
This landing page covers installation and basic usage. For further details on each command-line function, please refer to their individual documentation pages. Happy analyzing!
Source Code: Access the codebase or contribute to the project on GitHub.