Metabolite_AutoPlotter

Metabolite_AutoPlotter generates individual plots and processed outputs from quantified metabolite-intensity tables to visualize metabolite-level changes and support analysis of metabolomics and stable isotope tracing experiments.


Key Features:

  • Automated Plot Generation: Generates individual plots for each metabolite rather than bulk heat maps to enable per-metabolite inspection.
  • Flexible Input Handling: Accepts pre-processed metabolite-intensity tables and accommodates varying numbers of metabolites, conditions, and replicates.
  • Natural Abundance Correction: Performs natural abundance correction for stable isotope tracing data, including ^13C-labeled compounds.
  • Implementation: Implemented in R.
  • Efficient Output Management: Produces a zip file containing individual metabolite plots and restructured tables for downstream analysis.

Scientific Applications:

  • Stable Isotope Tracing: Supports analysis and interpretation of ^13C-labeling experiments through natural abundance correction and per-metabolite visualization.
  • Metabolomics Data Visualization: Provides per-metabolite plots to aid visualization and comparison of quantified metabolite intensities.
  • Systems Biology: Enables examination of metabolite-level changes relevant to systems biology studies.
  • Pharmacology and Clinical Research: Facilitates analysis and reporting of metabolite-level responses in pharmacology and clinical metabolomics studies.

Methodology:

Accepts pre-processed metabolite-intensity tables, generates individual metabolite plots, applies natural abundance correction for ^13C-labeled data, is implemented in R, and outputs a zip file containing plots and restructured tables.

Topics

Details

Tool Type:
command-line tool, library
Programming Languages:
R, C
Added:
1/18/2021
Last Updated:
9/3/2025

Operations

Data Inputs & Outputs

Publications

Pietzke M, Vazquez A. Metabolite AutoPlotter - an application to process and visualise metabolite data in the web browser. Cancer & Metabolism. 2020;8(1). doi:10.1186/s40170-020-00220-x. PMID:32670572. PMCID:PMC7350678.

PMID: 32670572
PMCID: PMC7350678
Funding: - Cancer Research UK: C596/A18076, C596/A21140