spectral-overlay-rendering-multi-sample
License: restricted — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution.
Summary
Render aligned peaks across multiple mass spectra as an interactive overlay or heatmap visualization with dynamic filtering controls. This skill enables real-time exploration of molecular networking peak alignments by allowing users to adjust intensity thresholds, alignment quality cutoffs, and peak presence criteria while observing live updates to the multi-spectrum display.
When to use
When you have aligned peak-alignment data from a preceding molecular networking task (structured as a table with peak intensity, m/z, retention time, and alignment quality metrics) and need to visualize and interactively filter peaks across multiple spectra to support comparative mass spectrometry analysis or quality assessment of alignments.
When NOT to use
- Input peaks have not yet been aligned across spectra—use alignment preprocessing step first
- You need static, non-interactive visualization—use a simpler plotting library or static report generation
- Peak data lacks alignment quality metrics or spectrum identity information—cannot stratify or color by spectrum
Inputs
- Aligned peak-alignment table (structured as CSV or in-memory DataFrame with columns: peak intensity, m/z, retention time, alignment quality metrics, spectrum identity)
- Filter parameters (intensity threshold, alignment score cutoff, peak presence/absence criteria)
- Multiple mass spectra identifiers or scan numbers
Outputs
- Interactive multi-spectrum visualization (overlay plot or heatmap)
- Real-time rendered peak display with user-adjustable filtering
- SVG export for high-resolution figures (optional)
How to apply
Load the aligned peak-alignment table into memory as a structured data frame with columns for intensity, m/z, retention time, alignment quality, and spectrum identity. Parse user-supplied filter parameters (e.g., intensity threshold slider, alignment score cutoff checkbox, peak presence/absence criteria) from the web interface. Apply row-wise boolean filtering to retain only peaks satisfying all active constraints. Render the filtered peak set using a web-capable charting library (Plotly, D3.js, or Canvas) with m/z on the x-axis, intensity on the y-axis, and spectrum identity encoded as color or facet. Attach interactive controls (sliders, checkboxes) to the rendering layer so users can dynamically adjust thresholds and see the visualization update in real-time. Validate that all displayed peaks pass the active filter criteria and that the rendering correctly represents the input alignment data without loss or corruption.
Related tools
- Plotly (Interactive charting library for rendering multi-spectrum overlay plots and heatmaps with real-time filter responsiveness)
- D3.js (Web-capable visualization framework for custom multi-spectrum alignment displays with dynamic filtering)
- Dash (Interactive web application framework used to build the filtering interface and connect filter controls to live visualization updates)
- Pandas (Data manipulation library for loading, filtering, and transforming aligned peak tables before rendering)
- Flask (Web framework hosting the visualization endpoints and API routes for spectrum retrieval and filtering) — github.com/Wang-Bioinformatics-Lab/NetworkFamily_MultipleAlignment_Website
Evaluation signals
- All displayed peaks satisfy the active filter criteria (e.g., intensity > threshold, alignment_score > cutoff); validate by spot-checking rendered points against filter state
- Visualization updates in real-time when user adjusts filter sliders or checkboxes without page reload
- Peak positions (m/z, intensity) in the rendered plot match the input aligned table exactly; compare plotted coordinates to input DataFrame
- Spectrum identity is correctly encoded (by color, facet, or overlay label) and all spectra in the filtered set are represented
- SVG export preserves all peak markers, axes, legend, and filter state annotations for reproducibility
Limitations
- Rendering performance may degrade with very large peak sets (> 10,000 aligned peaks); consider aggregation or downsampling strategies
- No changelog documented; version stability and backward compatibility of filter parameter schemas not specified
- Filter responsiveness depends on client-side browser performance; complex boolean logic across many spectra may introduce latency
Evidence
- [other] Load aligned peak-alignment data (from preceding molecular networking alignment task) into memory as a structured table with peak intensity, m/z, retention time, and alignment quality metrics.: "Load aligned peak-alignment data (from preceding molecular networking alignment task) into memory as a structured table with peak intensity, m/z, retention time, and alignment quality metrics."
- [other] Parse user-supplied filter parameters (intensity threshold, alignment score cutoff, peak presence/absence criteria) from the web interface input state.: "Parse user-supplied filter parameters (intensity threshold, alignment score cutoff, peak presence/absence criteria) from the web interface input state."
- [other] Apply row-wise filtering to the peak table using boolean logic on intensity and alignment-quality columns, retaining only peaks that satisfy all active filter constraints.: "Apply row-wise filtering to the peak table using boolean logic on intensity and alignment-quality columns, retaining only peaks that satisfy all active filter constraints."
- [other] Render the filtered peak set as an interactive multi-spectrum visualization (e.g., overlay plot or heatmap) with axes for m/z (x), intensity (y), and spectrum identity (color/facet), using a web-capable charting library (Plotly, D3.js, or Canvas).: "Render the filtered peak set as an interactive multi-spectrum visualization (e.g., overlay plot or heatmap) with axes for m/z (x), intensity (y), and spectrum identity (color/facet), using a"
- [other] Attach interactive filter controls (sliders, checkboxes) to the rendering layer so users can dynamically adjust thresholds and see the visualization update in real-time.: "Attach interactive filter controls (sliders, checkboxes) to the rendering layer so users can dynamically adjust thresholds and see the visualization update in real-time."
- [readme] Real-time peak alignment visualization with clickable peaks and set highlighting: "Real-time peak alignment visualization with clickable peaks and set highlighting"
- [readme] Custom spectrum ordering, m/z range filtering, and top-10 peak intensity analysis: "Custom spectrum ordering, m/z range filtering, and top-10 peak intensity analysis"
1---2name: spectral-overlay-rendering-multi-sample-23description: Use when when you have aligned peak-alignment data from a preceding molecular networking task (structured as a table with peak intensity, m/z, retention time, and alignment quality metrics) and need to visualize and interactively filter peaks across multiple spectra to support comparative mass.4license: CC-BY-4.05---67# spectral-overlay-rendering-multi-sample89> **License: restricted** — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution. <!-- asb-license-banner -->10## Summary1112Render aligned peaks across multiple mass spectra as an interactive overlay or heatmap visualization with dynamic filtering controls. This skill enables real-time exploration of molecular networking peak alignments by allowing users to adjust intensity thresholds, alignment quality cutoffs, and peak presence criteria while observing live updates to the multi-spectrum display.1314## When to use1516When you have aligned peak-alignment data from a preceding molecular networking task (structured as a table with peak intensity, m/z, retention time, and alignment quality metrics) and need to visualize and interactively filter peaks across multiple spectra to support comparative mass spectrometry analysis or quality assessment of alignments.1718## When NOT to use1920- Input peaks have not yet been aligned across spectra—use alignment preprocessing step first21- You need static, non-interactive visualization—use a simpler plotting library or static report generation22- Peak data lacks alignment quality metrics or spectrum identity information—cannot stratify or color by spectrum2324## Inputs2526- Aligned peak-alignment table (structured as CSV or in-memory DataFrame with columns: peak intensity, m/z, retention time, alignment quality metrics, spectrum identity)27- Filter parameters (intensity threshold, alignment score cutoff, peak presence/absence criteria)28- Multiple mass spectra identifiers or scan numbers2930## Outputs3132- Interactive multi-spectrum visualization (overlay plot or heatmap)33- Real-time rendered peak display with user-adjustable filtering34- SVG export for high-resolution figures (optional)3536## How to apply3738Load the aligned peak-alignment table into memory as a structured data frame with columns for intensity, m/z, retention time, alignment quality, and spectrum identity. Parse user-supplied filter parameters (e.g., intensity threshold slider, alignment score cutoff checkbox, peak presence/absence criteria) from the web interface. Apply row-wise boolean filtering to retain only peaks satisfying all active constraints. Render the filtered peak set using a web-capable charting library (Plotly, D3.js, or Canvas) with m/z on the x-axis, intensity on the y-axis, and spectrum identity encoded as color or facet. Attach interactive controls (sliders, checkboxes) to the rendering layer so users can dynamically adjust thresholds and see the visualization update in real-time. Validate that all displayed peaks pass the active filter criteria and that the rendering correctly represents the input alignment data without loss or corruption.3940## Related tools4142- **Plotly** (Interactive charting library for rendering multi-spectrum overlay plots and heatmaps with real-time filter responsiveness)43- **D3.js** (Web-capable visualization framework for custom multi-spectrum alignment displays with dynamic filtering)44- **Dash** (Interactive web application framework used to build the filtering interface and connect filter controls to live visualization updates)45- **Pandas** (Data manipulation library for loading, filtering, and transforming aligned peak tables before rendering)46- **Flask** (Web framework hosting the visualization endpoints and API routes for spectrum retrieval and filtering) — github.com/Wang-Bioinformatics-Lab/NetworkFamily_MultipleAlignment_Website4748## Evaluation signals4950- All displayed peaks satisfy the active filter criteria (e.g., intensity > threshold, alignment_score > cutoff); validate by spot-checking rendered points against filter state51- Visualization updates in real-time when user adjusts filter sliders or checkboxes without page reload52- Peak positions (m/z, intensity) in the rendered plot match the input aligned table exactly; compare plotted coordinates to input DataFrame53- Spectrum identity is correctly encoded (by color, facet, or overlay label) and all spectra in the filtered set are represented54- SVG export preserves all peak markers, axes, legend, and filter state annotations for reproducibility5556## Limitations5758- Rendering performance may degrade with very large peak sets (> 10,000 aligned peaks); consider aggregation or downsampling strategies59- No changelog documented; version stability and backward compatibility of filter parameter schemas not specified60- Filter responsiveness depends on client-side browser performance; complex boolean logic across many spectra may introduce latency6162## Evidence6364- [other] Load aligned peak-alignment data (from preceding molecular networking alignment task) into memory as a structured table with peak intensity, m/z, retention time, and alignment quality metrics.: "Load aligned peak-alignment data (from preceding molecular networking alignment task) into memory as a structured table with peak intensity, m/z, retention time, and alignment quality metrics."65- [other] Parse user-supplied filter parameters (intensity threshold, alignment score cutoff, peak presence/absence criteria) from the web interface input state.: "Parse user-supplied filter parameters (intensity threshold, alignment score cutoff, peak presence/absence criteria) from the web interface input state."66- [other] Apply row-wise filtering to the peak table using boolean logic on intensity and alignment-quality columns, retaining only peaks that satisfy all active filter constraints.: "Apply row-wise filtering to the peak table using boolean logic on intensity and alignment-quality columns, retaining only peaks that satisfy all active filter constraints."67- [other] Render the filtered peak set as an interactive multi-spectrum visualization (e.g., overlay plot or heatmap) with axes for m/z (x), intensity (y), and spectrum identity (color/facet), using a web-capable charting library (Plotly, D3.js, or Canvas).: "Render the filtered peak set as an interactive multi-spectrum visualization (e.g., overlay plot or heatmap) with axes for m/z (x), intensity (y), and spectrum identity (color/facet), using a"68- [other] Attach interactive filter controls (sliders, checkboxes) to the rendering layer so users can dynamically adjust thresholds and see the visualization update in real-time.: "Attach interactive filter controls (sliders, checkboxes) to the rendering layer so users can dynamically adjust thresholds and see the visualization update in real-time."69- [readme] Real-time peak alignment visualization with clickable peaks and set highlighting: "Real-time peak alignment visualization with clickable peaks and set highlighting"70- [readme] Custom spectrum ordering, m/z range filtering, and top-10 peak intensity analysis: "Custom spectrum ordering, m/z range filtering, and top-10 peak intensity analysis"
HolobiomicsLab