simphyni 0.1.7

SimPhyni: a tool for phylogenetic trait simulation and inference.

SimPhyNI

Overview

SimPhyNI (Simulation-based Phylogenetic iNteraction Inference) is a phylogenetically-aware framework for detecting evolutionary associations between binary traits (e.g., gene presence/absence, major/minor alleles, binary phenotypes) on microbial phylogenetic trees. This tool leverages phylogenetic infromation to correct for surious associations caused by the relatedness of sister taxa.

This pipeline is designed to:

• Infer evolutionary parameters for traits (gain/loss rates, time to emergence, ancestral states)
• Estimate trait co-occurence null models through independent simulation of traits
• Output statistical results for associations

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Getting Started

Installation

First create a new environment:

conda create -n simphyni python=3.11
conda activate simphyni

then install using using PyPI

pip install simphyni

test installation:

simphyni version

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Usage

Run mode (single-run)

simphyni run \
  --sample-name my_sample \
  --tree path/to/tree.nwk \
  --traits path/to/traits.csv \
  --run-traits 0,1,2 \
  --outdir my_analysis \
  --cores 4 \
  --temp_dir ./tmp \
  --min_prev 0.05 \
  --max_prev 0.95 \
  --prefilter \
  --plot

• --run-traits specifies a comma-separated list of column indices (0-indexed) in the traits CSV for “trait against all” comparisons. Use 'ALL' (default) to include all traits.

Run mode (batch)

Create a samples.csv file:

Sample,Tree,Traits,run_traits,MinPrev,MaxPrev
run1,tree1.nwk,traits1.csv,All,0.05,0.95
run2,tree2.nwk,traits2.csv,"0,1,2",0.05,0.90

• run_traits, MinPrev, and MaxPrev are optional columns that will use default values if not provided

Then execute:

simphyni run --samples samples.csv --cores 16

Run with HPC

First, download example cluster scripts:

simphyni download-cluster-scripts

Edit cluster config file for your computing cluster then install the approprate snakemake executor from the avalible catalog: https://snakemake.github.io/snakemake-plugin-catalog/index.html (slurm shown below):

pip install snakemake-executor-plugin-slurm

run simphyni with the --profile flag:

simphyni run --samples samples.csv --profile cluster_profile

For all run options:

simphyni run --help

Example data

Download and run example inputs using:

simphyni download-examples
simphyni run --samples example_inputs/simphyni_sample_info.csv --cores 8 --prefilter --plot

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Outputs

Outputs for each sample are placed in structured folders in the working directory or specified output directory in subdirectories by sample name, including:

• simphyni_result.csv contianing all tested trait pairs with their infered interaction direction, p-value, and effect size
• simphyni_object.pkl optional file containing the completed analysis, parsable with an active SimPhyNI evironment. Contorlled with the --save-object flag (not recommended for large analyses, > 1,000,000 comparisons)
• heatmap summaries of tested associations if --plot is enabled

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Directory Structure

SimPhyNI/
├── simphyni/               # Core package
│   ├── Simulation/         # Simulation scripts
│   ├── scripts/            # Workflow scripts
│   └── envs/simphyni.yaml  # Conda environment (used in snakemake)
├── conda-recipe/           # Build recipe 
├── cluster_scripts         # Cluster configs for SLURM
├── example_inputs 
└── pyproject.toml

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Contact

For questions, please open an issue or contact Ishaq Balogun at https://github.com/jpeyemi.