DIA-NN EasyFilter: KNIME Workflow for Proteomics Data Filtering and Visualization

A KNIME-based workflow for the critical assessment and visualization of DIA-NN proteomics analysis outcomes. The tool, developed by Gontse Mabuse Moagi, is designed to filter and explore quantitative protein characterization data from liquid chromatography-tandem mass spectrometry (LC–MS/MS) experiments. The dataset, last updated on 2026-04-27, is a 3.3 MB XLSX file.

Use Cases

• Filter proteomics data based on chromatographic peak quality, as mentioned in the description
• Assess data quality and quantity using integrated modules described in the workflow
• Explore qualitative and quantitative patterns in proteomics datasets via interactive visualization tools
• Remove contaminants using curated libraries integrated into the workflow

Strengths

• Workflow is optimized for efficient execution in the KNIME local desktop environment
• Integrates multiple features: chromatographic peak filtering, contaminant libraries, and quality assessment
• Demonstrated utility and robustness using published large-scale proteomics datasets, showing high comparability across studies

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Data may reflect temporal or source bias inherent to the demonstration datasets used

Provenance

Source

figshare

Collection Method

Developed as a software workflow (DIA-NN EasyFilter) for processing proteomics data.

Time Range

Demonstrated using published datasets, but no specific temporal coverage for the provided XLSX file.

Freshness

Last updated 2026-04-27 20:05:51

Geography

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