Locusviz

D 60 completed
Other
unknown / r · small
94
Files
4,275
LOC
0
Frameworks
4
Languages

Pipeline State

completed
Run ID
#1526247
Phase
done
Progress
0%
Started
2026-04-16 14:28:20
Finished
2026-04-16 14:28:20
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
17.27
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47862
Member of a group with 185 similar repo(s) — canonical #1559941 view group →
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AI Prompt

Create an R package called 'locusviz' for generating publication-quality, LocusZoom-style visualizations of GWAS data. The tool needs to support multi-panel plots combining Manhattan plots, fine-mapping results, LD patterns, and gene tracks. I need functions to handle flexible data input for GWAS summary statistics and fine-mapping outputs, while supporting both hg19 and hg38 genome builds. Key functions should include `plot_locuszoom()`, `plot_manhattan_panel()`, and `plot_fm_panel()`. Also include data processing utilities like `preprocess()` and `liftover_variant()` to standardize the input data.
r gwas visualization bioinformatics ggplot2 locuszoom genomics statistics r-package
Generated by gemma4:latest

Catalog Information

Create an R package called 'locusviz' for generating publication-quality, LocusZoom-style visualizations of GWAS data. The tool needs to support multi-panel plots combining Manhattan plots, fine-mapping results, LD patterns, and gene tracks. I need functions to handle flexible data input for GWAS summary statistics and fine-mapping outputs, while supporting both hg19 and hg38 genome builds. Key functions should include plot_locuszoom(), plot_manhattan_panel(), and plot_fm_panel(). Also inc

Tags

r gwas visualization bioinformatics ggplot2 locuszoom genomics statistics r-package

Quality Score

D
59.8/100
Structure
55
Code Quality
67
Documentation
55
Testing
15
Practices
78
Security
100
Dependencies
70

Strengths

  • CI/CD pipeline configured (github_actions)
  • Consistent naming conventions (snake_case)
  • Good security practices — no major issues detected
  • Properly licensed project

Weaknesses

  • No tests found — high risk of regressions
  • 299 duplicate lines detected — consider DRY refactoring

Recommendations

  • Add a test suite — start with critical path integration tests
  • Add a linter configuration to enforce code style consistency

Languages

r
94.2%
markdown
3.5%
yaml
1.2%
python
1.1%

Frameworks

None detected

Symbols

variable2
function1

Quality Timeline

1 quality score recorded.

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BinComp Dependency Hardening

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1 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
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