Software Dependency Management And Environment Setup

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"