Metabolomics Navigator Tools, strategies & workflow guidance for metabolomics

Quality control and filtering

metaboprep

An R package for importing processed metabolomics data, applying standardized sample and feature quality-control filters, and generating summary tables and HTML reports.

Platform-independentTargeted metabolomicsUntargeted metabolomicsR packageOpen source
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Overview

metaboprep prepares quantified metabolomics tables for downstream analysis by summarizing data, filtering samples/features and reporting QC decisions. Its R interface supports abundance matrices and vendor/service tabular exports with sample and feature annotations.

What can this tool do?

Feature selection

Common uses

  • Apply missingness, total-abundance, and PCA-based QC rules to processed metabolomics datasets.
  • Produce standardized QC summaries and reports before statistical analysis.

Scientific fit

Primary function

Quality control and filtering

Other functions

Visualization and reporting, Data management and sharing

Analysis types

Targeted metabolomics, Untargeted metabolomics

Data compatibility

Inputs

Feature or peak table, Sample metadata

Outputs

Feature or peak table, Statistical results, Human-readable report

Input formats

CSV or TSV, Other, Excel

Output formats

CSV or TSV, Other, HTML report

Scope and considerations

Designed for

  • Quality control and filtering of already quantified metabolomics tables.

Not designed for

  • Raw chromatographic peak detection or automatic correction of every analytical batch effect.

Important requirements

  • R and package dependencies, quantified abundance data and aligned sample/feature metadata; select importer and QC thresholds appropriate to the input structure.

Considerations

  • Missingness and outlier thresholds can remove biological signals; review exclusion reasons and compare pre/post-QC data before statistical modelling.

Access and documentation

Primary accessSource repository

Package DESCRIPTION declares MIT plus the accompanying LICENSE file. Document the installed version because current development interfaces can differ from the original paper.

License: MIT

Evidence and review

Enveda intake rechecked against official README/documentation, repository access terms and primary publication metadata on 2026-10-27. Editorial source review only; no software execution or independent benchmarking. See docs/enveda-expansion-review-2026-10-27.md.

Core publications

Resource papers, direct updates and tool-specific methods. Selection policy.

  1. metaboprep: an R package for preanalysis data description and processing. Bioinformatics (2022). doi:10.1093/bioinformatics/btac059

Related tools

dbnormSimilar function · Compare statistical batch-correction models and inspect technical variation in metabolomics matrices.InjectionDesignSimilar function · A web service for designing LC-MS and GC-MS multi-omics injection sequences with QC placement, inter-batch balancing, intra-batch randomization, and downloadable worksheets.IonToolPackSimilar function · IonToolPack groups graphical mass-spectrometry utilities for raw-data visualization, PeakQC quality assessment, tandem-library matching, targeted MS1 extraction and feature-list comparison.ISFragSimilar function · ISFrag recognizes candidate in-source fragments in LC-MS data by combining feature relationships and available MS/MS evidence.

Entry history

Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.

  1. 2026-10-27 · First committed entry

    Add 27 source-reviewed tools from Enveda intake

    View change · Entry at this revision

Full GitHub history