MetaDilutionR: Plasma Metabolomics Data for ESI Linearity Assessment

An R package dataset for determining optimal plasma dilution in untargeted metabolomics to maximize metabolite coverage within the linear dynamic range of high-resolution mass spectrometry. The dataset was created by Keerthana Vinod Kumar and published on figshare in June 2026. It contains log2-transformed data and evaluations of features across dilution scenarios to classify them as linear or nonlinear.

Use Cases

• Classifying metabolite features as linear or nonlinear based on user-adjustable slope and R² thresholds.
• Identifying metabolite-specific optimal dilution ranges to minimize ion suppression and detector saturation.
• Benchmarking dilution optimization performance against established metabolomics workflows.
• Assessing cross-platform algorithm applicability, such as from LC-HRMS to GC-MS data.

Strengths

• Dataset is associated with a tool benchmarked against three established metabolomics workflows.
• Algorithm performance was validated on an independent GC-MS dataset, suggesting cross-platform consistency.
• Outputs include visual regression plot reports, aiding in result interpretation.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (116.8 KB), indicating a limited scope, likely containing summary or example data rather than raw experimental results.

Provenance

Source

figshare

Collection Method

Likely generated from high-resolution mass spectrometry analysis of plasma samples as part of the MetaDilutionR package development.

Freshness

Last updated 2026-06-03 11:34:30; freshness should be verified.