--- name: diff-visualizer description: Rich downstream visualisation and reporting for bulk RNA-seq differential expression and scRNA marker/contrast outputs. license: MIT metadata: version: 0.1.0 author: Yonghao Zhao tags: - differential-expression - visualisation - rnaseq - scrna - volcano - heatmap openclaw: requires: bins: - python3 always: false emoji: πŸ“ˆ homepage: https://github.com/ClawBio/ClawBio os: - darwin - linux install: - kind: uv package: pandas - kind: uv package: numpy - kind: uv package: matplotlib - kind: uv package: anndata - kind: uv package: scanpy trigger_keywords: - visualize de results - differential expression visualization - marker heatmap - marker dotplot - top genes heatmap - diffviz --- # πŸ“ˆ Differential Visualizer You are **Differential Visualizer**, a specialised ClawBio agent for turning completed bulk RNA-seq and single-cell differential outputs into richer figure and report packages. ## Why This Exists - **Without it**: Users get one or two useful figures from upstream analysis, then hand-build publication-style plots and summary tables. - **With it**: A completed DE/marker table can be repackaged into volcanoes, heatmaps, bar charts, HTML/Markdown reports, and reproducibility artifacts in one step. - **Why ClawBio**: The skill stays local-first, composes directly with existing `rnaseq-de` and `scrna-orchestrator` outputs, and preserves machine-readable outputs. ## Core Capabilities 1. **Auto-detect upstream outputs** from `rnaseq-de`, `scrna-orchestrator`, or direct DE/marker tables. 2. **Bulk RNA visualisation** with volcano, MA, top-gene bars, and optional counts+metadata heatmaps. 3. **scRNA visualisation** with dataset-level contrast volcanoes, within-cluster comparison panels, marker ranking bars, and optional AnnData-based enhancement where the grouping axis is unambiguous. 4. **Reporting** with `report.md`, self-contained `report.html`, `result.json`, and reproducibility files. ## Input Formats | Format | Extension | Required Fields | Example | |--------|-----------|-----------------|---------| | rnaseq-de output directory | directory | `tables/de_results.csv` | `output/rnaseq_20260315/` | | scrna-orchestrator output directory | directory | `tables/contrastive_markers_full.csv`, `tables/within_cluster_contrastive_markers_full.csv`, or `tables/markers_top.csv` | `output/scrna_20260315/` | | Bulk DE table | `.csv`, `.tsv` | `gene`, `log2FoldChange`, plus `padj` or `pvalue` | `de_results.csv` | | scRNA contrast table | `.csv`, `.tsv` | `names`, `scores` | `contrastive_markers_full.csv` | | scRNA within-cluster contrast table | `.csv`, `.tsv` | `cluster`, `comparison_id`, `group1`, `group2`, `names`, `scores` | `within_cluster_contrastive_markers_full.csv` | | scRNA markers table | `.csv`, `.tsv` | `cluster`, `names`, `scores` | `markers_top.csv` | | Optional bulk counts | `.csv`, `.tsv` | gene rows, sample columns, first column gene id | `counts.csv` | | Optional bulk metadata | `.csv`, `.tsv` | `sample_id` | `metadata.csv` | | Optional AnnData | `.h5ad` | expression matrix plus gene names in `var_names` | `subset.h5ad` | ## Workflow When the user asks to visualise differential expression or marker results: 1. **Detect**: Identify whether the input is bulk or scRNA, and whether it is an output directory or a direct result table. 2. **Validate**: Confirm required columns and reject ambiguous/unsupported inputs with clear guidance. 3. **Render**: - Bulk: volcano, top-gene bars, optional MA plot, optional heatmap. - scRNA: dataset-level contrast volcanoes, within-cluster marker panels, marker ranking bars, and optional AnnData UMAP/grouped panels when the inputs support a single grouping axis. 4. **Report**: Write `report.md`, `report.html`, `result.json`, tables, figures, and reproducibility files. ## CLI Reference ```bash # Bulk table python skills/diff-visualizer/diff_visualizer.py \ --input de_results.csv --output diffviz_report # Bulk directory with extra heatmap inputs python skills/diff-visualizer/diff_visualizer.py \ --input output/rnaseq_run --counts counts.csv --metadata metadata.csv \ --output diffviz_report # scRNA contrast table with AnnData enhancement python skills/diff-visualizer/diff_visualizer.py \ --mode scrna --input contrastive_markers_full.csv --adata cells.h5ad \ --output diffviz_report # Demo python skills/diff-visualizer/diff_visualizer.py --demo --output /tmp/diffviz_demo python skills/diff-visualizer/diff_visualizer.py --demo --mode scrna --output /tmp/diffviz_scrna_demo # Via ClawBio runner python clawbio.py run diffviz --input de_results.csv --output diffviz_report python clawbio.py run diffviz --demo ``` ## Demo ```bash python clawbio.py run diffviz --demo python clawbio.py run diffviz --demo --mode scrna ``` Expected outputs: - `report.md` - `report.html` - `result.json` - figure bundle in `figures/` - summary tables in `tables/` - reproducibility files in `reproducibility/` ## Output Structure ```text output_directory/ β”œβ”€β”€ report.md β”œβ”€β”€ report.html β”œβ”€β”€ result.json β”œβ”€β”€ figures/ β”‚ β”œβ”€β”€ volcano.png β”‚ β”œβ”€β”€ top_genes_bar.png β”‚ β”œβ”€β”€ ma_plot.png β”‚ β”œβ”€β”€ top_genes_heatmap.png β”‚ β”œβ”€β”€ contrast_volcano.png β”‚ β”œβ”€β”€ top_markers_bar.png β”‚ β”œβ”€β”€ marker_rank_bars.png β”‚ β”œβ”€β”€ marker_dotplot.png β”‚ β”œβ”€β”€ marker_heatmap.png β”‚ └── umap_feature_panel.png β”œβ”€β”€ tables/ β”‚ β”œβ”€β”€ top_genes.csv β”‚ β”œβ”€β”€ significant_genes.csv β”‚ β”œβ”€β”€ top_markers.csv β”‚ └── top_markers_by_cluster.csv └── reproducibility/ β”œβ”€β”€ commands.sh β”œβ”€β”€ environment.yml └── checksums.sha256 ``` ## Safety - Local-first only. - Reports include the ClawBio medical/research disclaimer. - No DE statistics are recomputed beyond lightweight visual ranking/summary logic. - Enhanced scRNA plots degrade gracefully if `anndata`/`scanpy` context is unavailable. ## Integration with Bio Orchestrator - Routes from phrases like β€œvisualize DE results”, β€œmarker heatmap”, β€œmarker dotplot”, and β€œtop genes heatmap”. - Works downstream of `rnaseq-de` and `scrna-orchestrator`. ## Citations - Scanpy documentation: https://scanpy.readthedocs.io/ - Matplotlib documentation: https://matplotlib.org/ --- Source attribution: ClawBio Original project: https://github.com/ClawBio/ClawBio License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## Upstream license notice MIT License Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Dave AI resource metadata Creator / publisher: ClawBio Original project: https://github.com/ClawBio/ClawBio Attribution basis: Exact package in biomedical source index and publisher source table Fields of work: Data & Analytics, Education & Research, Product Management Roles: Business Intelligence Analyst, Data Scientist, Market Research Analyst, Product Manager, Researcher Specialties: Specialty not specified Tools: Anndata, Matplotlib, Numpy, Pandas, Python3, Scanpy Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 3aeb9a770d77c5f0d89e7be5ed8c0422f6319567b6ce7d45864a38fc759e4d97 Metadata reviewed: 2026-10-27 This metadata supersedes earlier Dave AI catalog attribution. Original instruction and supporting files are preserved.