Quality control and filtering

MatrixQCvis

Explore sample and feature quality in metabolomics matrices through interactive visualizations.

Platform-independentR packageWeb applicationOpen source

Overview

MatrixQCvis is a Bioconductor/Shiny interface for inspecting quantitative matrices. It visualizes distributions, sample relationships, outliers and batch structure, using SummarizedExperiment as its input container.

What can this tool do?

Interactive dashboard

Common uses

  • Inspect processed MS-metabolomics matrices before interpretation.

Scientific fit

Primary function

Quality control and filtering

Data compatibility

Inputs

Feature or peak table, Sample metadata

Outputs

Human-readable report

Input formats

SummarizedExperiment object supplied directly or as an RDS file

Output formats

Interactive per-sample and per-feature quality visualizations

Scope and considerations

Designed for

  • Explore sample and feature quality in metabolomics matrices through interactive visualizations.

Not designed for

  • Confirming compound identity or replacing study design and scientific review.

Important requirements

  • A feature-by-sample matrix and metadata prepared as a SummarizedExperiment object.

Considerations

  • Visual separation alone cannot determine whether a batch difference is technical or biological.
  • Use the compatible Bioconductor release rather than assuming the development branch is production-ready.

Access and documentation

License checked against official package metadata or repository. Local setup requires the documented dependencies; no installation or hosted-service availability test was performed.

License: GPL-3.0

Evidence and review

Enveda intake candidate verified against official documentation, source/package metadata and primary-publication DOI/title/year on 2026-10-02. Editorial review only; no software execution or independent benchmark.

Core publications

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

  1. MatrixQCvis: shiny-based interactive data quality exploration for omics data. Bioinformatics (2021). doi:10.1093/bioinformatics/btab748

    Published online in 2021; assigned to the 2022 journal issue. Replaces the intake preprint citation.

Related tools

Entry history

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

  1. 2026-10-05 · First committed entry

    Add seven source-validated QC tools and Enveda intake ledger

    View change · Entry at this revision

Full GitHub history