# Software Dependency Management And Environment Setup

> Use when you are preparing to run the MetaboDirect pipeline for the first time on a new machine, or you need to reproduce a published benchmark or analysis on a different OS (Windows, Linux, MacOS) and want to guarantee that all six pipeline steps (data pre-processing, diagnostics, exploration.

- Skill: `holobiomicslab/software-dependency-management-and-environment-setup` (Agent Skill)
- Install (CLI): `npx skillmds@latest add holobiomicslab/software-dependency-management-and-environment-setup`
- Raw SKILL.md: https://api.skillmd.com/api/skills/holobiomicslab/software-dependency-management-and-environment-setup/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- License: CC-BY-4.0
- Author: HolobiomicsLab (https://skillmd.com/u/holobiomicslab)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/holobiomicslab/software-dependency-management-and-environment-setup

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# software-dependency-management-and-environment-setup

## Summary

Install and configure MetaboDirect and its runtime dependencies (Python, R, Cytoscape with specific libraries) to ensure a reproducible computational environment for FT-ICR MS data analysis. This skill is essential because MetaboDirect's pipeline integrates multiple languages and external tools, and version mismatches or missing libraries cause silent failures or incomplete output.

## When to use

You are preparing to run the MetaboDirect pipeline for the first time on a new machine, or you need to reproduce a published benchmark or analysis on a different OS (Windows, Linux, MacOS) and want to guarantee that all six pipeline steps (data pre-processing, diagnostics, exploration, chemodiversity, statistics, transformation networks) execute without missing dependencies or version conflicts.

## When NOT to use

- You are analyzing metabolomic data in a different format (e.g., mzML or netCDF raw spectra) that has not already been processed through Formularity or CoreMS to produce assigned molecular formulas in .csv format—MetaboDirect expects pre-assigned formulas as input, not raw mass spectrometry data.
- Your analysis goal requires only visualization or post-hoc statistical comparison of already-computed diversity metrics; dependency setup is unnecessary overhead if you are reusing pre-computed outputs.
- You are running on a shared HPC cluster with pre-installed module systems (e.g., Lmod or Environment Modules) where a system administrator has already configured a MetaboDirect environment module—use `module load metabodirect` instead of manual installation.

## Inputs

- Python interpreter (version ≥3.5)
- R interpreter (version ≥4)
- Cytoscape application (version ≥3.8) with FileTransfer plugin
- pip or Python package manager
- R library installation method (install.packages or conda)
- System PATH environment variable

## Outputs

- Functional MetaboDirect command-line tool accessible via `metabodirect` command
- Python environment with argparse, numpy, pandas, seaborn, more-itertools, py4cytoscape, statsmodels installed
- R environment with tidyverse, RColorBrewer, vegan, ggnewscale, ggpubr, KEGGREST, factoextra, UpSetR, pmartR, SYNCSA, ggvenn, ggrepel installed
- Cytoscape application with FileTransfer plugin enabled and py4cytoscape connectivity verified
- Test run report with pipeline execution time and confirmation that all six steps completed

## How to apply

Install MetaboDirect v0.3.4 from PyPI using `pip install metabodirect`, then verify that Python 3.5+ and R 4+ are in your PATH. Install R packages (tidyverse, RColorBrewer, vegan, ggnewscale, ggpubr, KEGGREST, factoextra, UpSetR, pmartR, SYNCSA, ggvenn, ggrepel) using R's install.packages() or a dependency manager. Install Cytoscape 3.8+ and the FileTransfer plugin separately; MetaboDirect calls py4cytoscape to communicate with it. Verify installation by running `metabodirect -h` and test the full pipeline on a small dataset (e.g., 4–40 samples) to confirm all six steps and optional KEGG annotation execute without errors. Record the wall-clock time for this test run to establish a baseline for performance validation.

## Related tools

- **MetaboDirect** (Primary command-line pipeline for FT-ICR MS analysis that orchestrates data pre-processing, diagnostics, exploration, chemodiversity, statistics, and transformation network generation) — https://github.com/Coayala/MetaboDirect
- **Python** (Runtime language for MetaboDirect core pipeline logic and dependency management via pip)
- **R** (Runtime language for statistical analysis (vegan, SYNCSA), visualization (ggpubr, ggnewscale), and KEGG database queries (KEGGREST))
- **Cytoscape** (Desktop application for visualization and interactive exploration of biochemical transformation networks generated by MetaboDirect; communicates via py4cytoscape)
- **py4cytoscape** (Python library that enables MetaboDirect to programmatically control Cytoscape for network visualization)
- **KEGGREST** (R package that queries the KEGG database to annotate mass-based transformations with putative metabolic pathways and modules)
- **vegan** (R package providing diversity metrics (alpha and beta diversity) used in chemodiversity analysis step)
- **SYNCSA** (R package providing community phylogenetic diversity and functional trait-based metrics for chemodiversity analysis)

## Examples

```
pip install metabodirect && metabodirect -h
```

## Evaluation signals

- Running `metabodirect -h` produces a help menu with all required arguments and does not raise ImportError or ModuleNotFoundError.
- All Python imports (numpy, pandas, seaborn, py4cytoscape, statsmodels) succeed without version conflicts when MetaboDirect executes.
- All R packages (tidyverse, vegan, SYNCSA, KEGGREST, ggpubr, ggnewscale, UpSetR, factoextra, pmartR, ggvenn, ggrepel) load successfully via `library()` within R scripts called by MetaboDirect.
- A test run on a small FT-ICR MS dataset (4–40 samples in Formularity .csv format) completes all six pipeline steps without hanging, timeout, or segmentation fault; wall-clock time for main pipeline on 40 samples is <1 minute, matching published benchmarks.
- Cytoscape launches and connects to MetaboDirect via py4cytoscape without authentication or socket errors; transformation networks render in the Cytoscape interface.

## Limitations

- MetaboDirect requires R 4 and above; installations on systems with R 3.x will fail to load tidyverse and modern packages, and downgrading R may break system package managers.
- Cytoscape 3.8+ must be installed and running as a separate desktop application; MetaboDirect cannot use Cytoscape if it is not in the user's PATH or if the FileTransfer plugin is not loaded, causing transformation network visualization to fail silently.
- KEGGREST queries are network-dependent and may timeout or return incomplete annotations if the KEGG REST API is unavailable or rate-limited; offline KEGG mirror or local database setup is not documented.
- Cross-platform path handling (Windows backslashes vs. Unix forward slashes) may cause issues if environment variables or shell commands are not properly escaped; testing on each target OS (Windows, Linux, MacOS) is recommended.
- Python 3.5 support is nominally specified but is outdated; NumPy and pandas have dropped Python 3.5 support in recent versions, so actual minimum Python version is likely 3.8 or higher.

## Evidence

- [readme] MetaboDirect requires Python (3.5 and above), R (4 and above) and Cytoscape (3.8 and above) with the following libraries/modules: "MetaboDirect requires Python (3.5 and above), R (4 and above) and Cytoscape (3.8 and above) with the following libraries/modules"
- [other] Install MetaboDirect (v0.3.4) via Python Package Index with dependencies NumPy, pandas, seaborn, py4cytoscape, and matplotlib, ensuring compatibility on the target OS (Windows, Linux, or MacOS).: "Install MetaboDirect (v0.3.4) via Python Package Index with dependencies NumPy, pandas, seaborn, py4cytoscape, and matplotlib, ensuring compatibility on the target OS (Windows, Linux, or MacOS)"
- [readme] MetaboDirect can be installed directly from PyPi using: pip install metabodirect: "MetaboDirect can be installed directly from PyPi using: pip install metabodirect"
- [readme] For more information please check the User Manual at metabodirect.readthedocs.io: "For more information please check the User Manual"
- [other] Run the main MetaboDirect pipeline (six steps: data pre-processing, data diagnostics, data exploration, chemodiversity analysis, statistical analysis, and transformation network analysis) on each of the 40-sample and 120-sample mock datasets using a single command, recording elapsed wall-clock time.: "Run the main MetaboDirect pipeline (six steps: data pre-processing, data diagnostics, data exploration, chemodiversity analysis, statistical analysis, and transformation network analysis) on each of"