IonFlow: a galaxy tool for the analysis of ionomics data sets

Area of Science:

• Biochemistry
• Bioinformatics
• Computational Biology

Background:

• Inductively coupled plasma mass spectrometry (ICP-MS) generates complex, multi-dimensional datasets.
• Specialized data analysis tools are essential for interpreting ICP-MS outputs, particularly for ionomics.

Purpose of the Study:

• To introduce IonFlow, a novel Galaxy tool designed for ionomics data analysis.
• To provide a user-friendly pipeline for processing and interpreting high-throughput elemental profiling data.

Main Methods:

• IonFlow is an R-based pipeline integrated into the Galaxy platform.
• It processes raw ICP-MS data for elemental profiling.
• Utilizes multivariate statistical techniques (PCA, hierarchical clustering) and network algorithms (relevance networks, gene set enrichment analysis).

Main Results:

• The IonFlow pipeline effectively processes and analyzes ionomics data.
• Demonstrated utility on benchmark datasets from *S. Cerevisiae* and human HeLa cells.

Conclusions:

• IonFlow facilitates the exploration and interpretation of complex ionomics data.
• The tool is freely accessible, promoting wider adoption in elemental profiling research.