feat(bokeh): implement manhattan-gwas

[github-actions]

Implementation: manhattan-gwas - bokeh

Implements the bokeh version of manhattan-gwas.

File: plots/manhattan-gwas/implementations/bokeh.py

Parent Issue: #2925

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a Manhattan plot for GWAS data with approximately 44,000 SNPs across 22 chromosomes. The x-axis shows genomic position with chromosome numbers (1-22) labeled below. The y-axis shows -log₁₀(p-value) ranging from 0 to about 12. Points use alternating blue shades (darker #306998 and lighter #7BA3C9) for adjacent chromosomes, creating visual separation. Significant SNPs above the genome-wide threshold are highlighted in yellow/gold (#FFD43B) and are larger in size. Two horizontal threshold lines are present: a red dashed line at ~7.3 for genome-wide significance (p = 5×10⁻⁸) and a teal/green dotted line at 5 for suggestive threshold (p = 1×10⁻⁵). The title "manhattan-gwas · bokeh · pyplots.ai" appears in the top-left. The background is light gray (#FAFAFA). Significant peaks are visible on chromosomes 2, 6, 11, and 17 as specified in the data generation. Bokeh interactive tools are visible in the top-right corner.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title and axis labels are readable, but some text on the right side is small
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (7/8) - Point sizes are appropriate for data density; significant SNPs clearly visible with larger markers
• VQ-04: Color Accessibility (5/5) - Blue/light-blue alternating scheme is colorblind-safe, yellow highlights are distinct
• VQ-05: Layout Balance (4/5) - Good use of canvas space, minor issue with data concentrated in lower portion
• VQ-06: Axis Labels (2/2) - Descriptive labels: "Genomic Position" and "-log₁₀(p-value)"
• VQ-07: Grid & Legend (1/2) - Grid is subtle, but no legend explaining the color scheme for significant vs non-significant SNPs

Spec Compliance (23/25 pts)

• SC-01: Plot Type (8/8) - Correct Manhattan plot type
• SC-02: Data Mapping (5/5) - Cumulative genomic position on X, -log10(p-value) on Y
• SC-03: Required Features (4/5) - Has significance thresholds, alternating colors, significant SNP highlighting; missing optional SNP labels
• SC-04: Data Range (3/3) - Y-axis shows all data including most significant SNPs
• SC-05: Legend Accuracy (1/2) - No legend for color coding
• SC-06: Title Format (2/2) - Correct format: "manhattan-gwas · bokeh · pyplots.ai"

Data Quality (19/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows significant peaks on multiple chromosomes, realistic p-value distribution
• DQ-02: Realistic Context (7/7) - Simulated GWAS data is a standard, neutral scientific context
• DQ-03: Appropriate Scale (5/5) - Realistic chromosome sizes, p-values range appropriately

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Simple script: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - All imports are used
• CQ-04: No Deprecated API (1/1) - Uses current Bokeh API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Uses ColumnDataSource, interactive tools (pan, zoom), Span for threshold lines, but could leverage more Bokeh features like HoverTool

Strengths

• Excellent implementation of Manhattan plot with proper chromosome coloring and cumulative positioning
• Good use of Bokeh interactive tools (pan, zoom, save) for exploration of GWAS data
• Clear threshold lines with labels for genome-wide and suggestive significance levels
• Appropriate point sizing differentiation between significant and non-significant SNPs
• Clean, KISS-compliant code structure with proper reproducibility

Weaknesses

• Missing legend to explain color coding (blue/light blue for chromosomes, yellow for significant)
• Could add HoverTool to show SNP details on mouseover, which is a key Bokeh strength

Verdict: APPROVED