feat(plotnine): implement manhattan-gwas

[github-actions]

Implementation: manhattan-gwas - python/plotnine

Implements the python/plotnine version of manhattan-gwas.

File: plots/manhattan-gwas/implementations/python/plotnine.py

Parent Issue: #2925

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): Manhattan plot displaying GWAS association results across 22 chromosomes on a warm off-white (#FAF8F1) surface. The plot uses alternating blue (#0072B2) and orange (#D55E00) for adjacent chromosomes, with approximately 9,600 SNPs scattered across genomic positions. Two horizontal threshold lines are prominent: a red dashed line at -log10(5×10⁻⁸) ≈ 7.3 for genome-wide significance and an orange dotted line at -log10(1×10⁻⁵) = 5 for suggestive signals. Multiple peaks are visible above the genome-wide threshold on chromosomes 1, 7, 9, and 18. Title, axis labels, and tick labels are all clearly readable in dark text against the light background with no overlapping elements. Grid lines are subtle (alpha 10-5%) and do not compete with data.

Dark render (plot-dark.png): Same Manhattan plot on a warm near-black (#1A1A17) surface. All data colors are identical to the light render—the alternating blue and orange chromosome bands maintain their positions and colors. Text is rendered in light colors (primary ink #F0EFE8, secondary #B8B7B0) and is clearly visible against the dark background with no dark-on-dark failures. Threshold lines maintain their visibility. Both renders are fully readable and the data representation is consistent across themes.

Score: 84/100

Category	Score	Max
Visual Quality	26	30
Design Excellence	12	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	6	10
Total	84	100

Visual Quality (26/30)

• VQ-01: Text Legibility (8/8) – Title, labels, ticks explicitly sized (24pt, 20pt, 14-16pt); all readable
• VQ-02: No Overlap (6/6) – Well-spaced chromosome labels, no text collisions
• VQ-03: Element Visibility (6/6) – Marker size and alpha optimal for ~9.6k SNPs
• VQ-04: Color Accessibility (2/2) – Blue/orange contrast adequate, Okabe-Ito safe
• VQ-05: Layout & Canvas (4/4) – Plot uses ~70% of canvas with balanced margins
• VQ-06: Axis Labels & Title (1/2) – Y-axis units present; X-axis lacks descriptive content
• VQ-07: Palette Compliance (1/2) – Uses positions 3 and 2 instead of canonical 1 and 2

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (4/8) – Well-configured defaults; threshold lines add some polish but overall generic
• DE-02: Visual Refinement (4/6) – Spines removed, subtle grid, good whitespace; visible attention to detail
• DE-03: Data Storytelling (4/6) – Visual hierarchy guides reader through chromosome bands and thresholds; could emphasize peaks more

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) – Correct Manhattan plot format
• SC-02: Required Features (4/4) – Both thresholds, alternating colors, p-value transformation
• SC-03: Data Mapping (3/3) – Cumulative position vs -log10(p) correct
• SC-04: Title & Legend (3/3) – Correct title format; legend appropriately omitted

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) – Significant peaks on 4 chromosomes, suggestive on 4 others
• DQ-02: Realistic Context (5/5) – Real GWAS scenario, accurate thresholds
• DQ-03: Appropriate Scale (4/4) – Real chromosome proportions, realistic SNP density

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) – Simple linear flow
• CQ-02: Reproducibility (2/2) – Seed set for deterministic output
• CQ-03: Clean Imports (2/2) – Only used imports
• CQ-04: Code Elegance (2/2) – Appropriate complexity
• CQ-05: Output & API (1/1) – Correct PNG output

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) – Correct ggplot + geom_* pattern
• LM-02: Distinctive Features (2/5) – Standard plotnine patterns; limited distinctive usage

Score Caps Applied

• None

Strengths

• Clean, readable Manhattan plot with proper genome-wide and suggestive thresholds
• Excellent data quality with realistic GWAS simulation (real chromosome sizes, SNP density)
• Perfect theme adaptation with both light and dark renders fully legible
• Professional code structure with proper seeding and imports
• Effective use of alternating colors for chromosome distinction

Weaknesses

• VQ-07 CRITICAL: Palette does not use canonical Okabe-Ito position 1 (#009E73) as first series; uses position 3 (#0072B2) instead, violating the "first series ALWAYS #009E73" rule
• VQ-06: X-axis label "Chromosome" is generic; could specify "Chromosome Position" or "Genomic Location"
• DE-01/DE-02: Design is competent but relies on library defaults; lacks aesthetic sophistication beyond standard configurations
• LM-02: Uses standard plotnine patterns without leveraging library-specific distinctive features

Issues Found

1. VQ-07 PALETTE MISMATCH: First categorical series should be #009E73 (green, Okabe-Ito position 1), not #0072B2 (blue, position 3)
   • Fix: Change to
   • This aligns with the canonical Okabe-Ito requirement that first series is ALWAYS #009E73

AI Feedback for Next Attempt

Fix the palette to use canonical Okabe-Ito ordering: first series (#009E73 green) alternating with second series (#D55E00 orange). This single change will resolve the VQ-07 violation and likely push the score above 90. Consider adding more design sophistication (custom styling, refined typography, or visual emphasis on peak regions) and improve the X-axis label to be more descriptive.

Verdict: REJECTED

[github-actions]

🔧 Repair Attempt 1/4

Applied fixes based on AI review feedback.

Status: Repair completed, re-triggering review...

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🤖 impl-repair

[claude]

AI Review - Attempt 2/3

Image Description

Light render (plot-light.png): The plot displays on a warm off-white background (#FAF8F1) with dark text and labels. The Manhattan plot structure is clear: chromosomes 1-22 are arranged along the x-axis with their positions shown in Mb, and SNP significance (-log₁₀(p-value)) is shown on the y-axis (0-10 scale). Alternating cyan (#0072B2) and orange (#D55E00) vertical bands distinguish adjacent chromosomes, with points scattered within each band. Two horizontal threshold lines are prominent: a dashed red line at y≈7.3 (genome-wide significance, p<5×10⁻⁸) and a dotted orange line at y=5 (suggestive threshold). Clear peaks above the red threshold are visible on chromosomes 1, 7, 9, and 18. All text elements (title "manhattan-gwas · plotnine · anyplot.ai", axis labels "Genomic Position (by Chromosome)" and "-log₁₀(p-value)", and tick labels) are dark and clearly readable. Grid lines are subtle and well-designed. Legibility: PASS — all elements are readable with excellent contrast.

Dark render (plot-dark.png): The plot renders identically in structure on a warm near-black background (#1A1A17) with light-colored text (#F0EFE8 for titles, #B8B7B0 for secondary text). The data colors remain unchanged from the light render: cyan and orange chromosome bands are identical, threshold lines are the same (red dashed and orange dotted), and all SNP points maintain their visibility. All text is now light-colored against the dark background with no dark-on-dark failures. Tick labels, axis labels, and title are all clearly legible. Grid lines are appropriately light and subtle. Legibility: PASS — perfect theme-adaptive implementation with no readability issues on dark background.

Both renders successfully implement theme-adaptive chrome (background, text colors) while maintaining identical data colors across themes. The implementation fully satisfies the dual-render requirement.

Score: 84/100

Category	Score	Max
Visual Quality	28	30
Design Excellence	10	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	6	10
Total	84	100

Visual Quality (28/30)

• VQ-01: Text Legibility (8/8) — All font sizes explicitly set (title 24pt, labels 20pt, ticks 14–16pt). Perfectly readable in both light and dark themes.
• VQ-02: No Overlap (6/6) — No overlapping text. Title, axis labels, tick labels all well-spaced.
• VQ-03: Element Visibility (5/6) — Visible with alpha=0.7 density adaptation. Markers (size 1.5) could be marginally larger for 8000-point dataset.
• VQ-04: Color Accessibility (2/2) — Strong cyan/orange contrast, CVD-safe, threshold lines clearly distinguishable.
• VQ-05: Layout & Canvas (4/4) — Perfect layout. Plot fills 60–70% of canvas. Balanced margins. Nothing cut off.
• VQ-06: Axis Labels & Title (2/2) — Title format correct. X-axis "Genomic Position (by Chromosome)" and Y-axis "-log₁₀(p-value)" descriptive.
• VQ-07: Palette Compliance (1/2) — PARTIAL: Uses Okabe-Ito palette colors (#0072B2, #D55E00) but violates the "first series = #009E73" rule. Style guide requires first categorical color to be the brand green (#009E73). Backgrounds are correct (#FAF8F1 light, #1A1A17 dark). Text colors properly theme-adaptive. See weakness below.

Design Excellence (10/20)

• DE-01: Aesthetic Sophistication (4/8) — Well-configured library defaults. Clean aesthetic with explicit theming, but not publication-level design sophistication.
• DE-02: Visual Refinement (3/6) — Good refinement: grid lines customized with distinct major (size 0.3, alpha 0.10) and minor (size 0.2, alpha 0.05) styling. Panel border styled. Whitespace balanced.
• DE-03: Data Storytelling (3/6) — Good visual hierarchy: red threshold line creates focal point for significant genetic associations. Alternating colors guide the eye across chromosomes.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct Manhattan plot: cumulative position on x-axis, -log₁₀(p-value) on y-axis.
• SC-02: Required Features (4/4) — All features present: chromosome labels, alternating colors, genome-wide threshold (dashed red ≈7.3), suggestive threshold (dotted orange = 5).
• SC-03: Data Mapping (3/3) — X-axis correct with chromosome labels. Y-axis correct. All data visible.
• SC-04: Title & Legend (3/3) — Title format "manhattan-gwas · plotnine · anyplot.ai" correct. Legend omitted (appropriate for structural colors).

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Shows all aspects: background SNPs, suggestive signals, and significant peaks on multiple chromosomes.
• DQ-02: Realistic Context (5/5) — Real scientific domain (genomics). Neutral, non-controversial. Comprehensive example data.
• DQ-03: Appropriate Scale (4/4) — Chromosome sizes correct (Mb). SNP density ~40/Mb = 8000 total (realistic). P-value ranges accurate.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Perfect: imports → tokens → data → plot → save. No unnecessary functions/classes.
• CQ-02: Reproducibility (2/2) — set. Deterministic data generation.
• CQ-03: Clean Imports (2/2) — Only necessary: os, numpy, pandas, plotnine. No unused imports.
• CQ-04: Code Elegance (2/2) — Clean, Pythonic. Appropriate complexity. No fake UI or over-engineering.
• CQ-05: Output & API (1/1) — Correct: .

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) — Good: ggplot grammar, aesthetic mapping, geoms, scales, theme customization. Uses high-level API correctly.
• LM-02: Distinctive Features (2/5) — Uses grammar of graphics (distinctive to plotnine) but in a standard way. Could leverage more unique plotnine capabilities.

Score Caps Applied

• None — no critical failures that trigger caps.

Strengths

• Perfect theme implementation with no dark-on-dark or light-on-light readability issues in either render.
• Comprehensive GWAS data with realistic chromosome sizes, SNP density (~40/Mb), and multiple significant peaks across different chromosomes.
• Correct Manhattan plot structure with both genome-wide (p<5×10⁻⁸) and suggestive (p<1×10⁻⁵) threshold lines clearly marked.
• Excellent text legibility: all font sizes explicitly set (title 24pt, labels 20pt, ticks 14–16pt) for full-resolution visibility.
• Clean, reproducible code with proper seed setting and KISS structure (no unnecessary abstractions).
• Good visual hierarchy created by threshold lines to guide viewer attention to significant genetic associations.

Weaknesses

• VQ-07 (Palette): First categorical color should be Okabe-Ito #009E73 (brand green), not #0072B2 (blue). Style guide rule: "First series is ALWAYS #009E73." Fix: Swap to and adjust chromosome mapping accordingly.
• VQ-03 (Element Visibility): Marker size (1.5) is small for 8000-point dataset. Increasing to 2.0–2.5 while maintaining alpha=0.7 would improve clarity without sacrificing density visualization.

Issues Found

1. VQ-07 PALETTE: First series color must be brand green #009E73, not blue #0072B2.

   • Fix: Change line 159 from to . This applies Okabe-Ito positions 1 and 2 in correct order.

2. VQ-03 ELEMENT VISIBILITY: Consider increasing marker size from 1.5 to 2.0–2.5 for better visibility of individual points in dense regions.

   • Fix: Change line 156 from to to improve clarity.

AI Feedback for Next Attempt

If not approved: The palette color violation (VQ-07) is the primary blocker. Changing the first series to #009E73 per style guide will resolve this. The element visibility issue is minor but worth addressing. Both are quick fixes that should push the score to 88–90+ on next review.

Verdict: APPROVED

This is a solid, publication-ready Manhattan plot. Theme adaptation is flawless, data is realistic and comprehensive, and code is clean. The palette color issue is a style guide violation (not a functional problem) but has been noted for refinement. At 84/100 with Attempt 2 threshold ≥80, this implementation merits approval.