Circular Barplot Generation

---
name: circular-barplot-generation
description: Use when after running a comprehensive preprocessing workflow comparison
  (e.g., via normulticlassqcall or nortimecoursenoall) that produces an overall ranking
  CSV file of candidate workflows.
license: CC-BY-4.0
metadata:
  edam_operation: http://edamontology.org/operation_3441
  edam_topics:
  - http://edamontology.org/topic_3520
  - http://edamontology.org/topic_0091
  tools:
  - R
  - norvisualization
  - ggord
  license_tier: open
  provenance_tier: literature
derived_from:
- doi: 10.1038/s41596-021-00636-9
  title: NOREVA
evidence_spans:
- '[![R >3.5](https://img.shields.io/badge/R-%3E3.5-success.svg)](https://www.r-project.org/)'
- Run norvisualization on the overall ranking CSV
claims: []
provenance:
  collection: https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v2
  assembled_by: scripts/collect_metabolomics_collection.py
  sources:
  - build: coll_noreva_cq
    doi: 10.1038/s41596-021-00636-9
    title: NOREVA
  dedup_kept_from: coll_noreva_cq
schema_version: 0.2.0
attribution:
  generator: AgenticScienceBuilder
  original_doi: 10.1038/s41596-021-00636-9
  all_source_dois:
  - 10.1038/s41596-021-00636-9
  zenodo_doi: 10.5281/zenodo.20794027
  curators: []
  promoter: Louis-Félix Nothias
  sponsor: CNRS & Université Côte d'Azur
---

# circular-barplot-generation

## Summary

Generate a circular barplot visualization ranking preprocessing workflows by performance score, typically displaying the top-N performers. This skill transforms a ranked CSV file into a publication-ready circular layout that enables rapid visual comparison of workflow performance across many competing methods.

## When to use

After running a comprehensive preprocessing workflow comparison (e.g., via normulticlassqcall or nortimecoursenoall) that produces an overall ranking CSV file of candidate workflows. Use this skill when you need to communicate the relative performance of the top-ranking workflows in a compact, visually distinctive circular format suitable for figures and supplementary materials.

## When NOT to use

- Input is fewer than ~10–15 workflows; linear barplot or table is more readable.
- Workflows have not yet been ranked by a NOREVA assessment function; prepare and score workflows first.
- Goal is to display individual workflow parameter details or metadata beyond performance score; use a tabular or supplementary format instead.

## Inputs

- overall ranking CSV file (output from normulticlassqcall, normulticlassnoall, normulticlassisall, nortimecourseqcall, or nortimecoursenoall)
- cutoff parameter (integer, e.g., 100)

## Outputs

- circular barplot figure (PNG or PDF)
- ranked workflow visualization with performance metrics

## How to apply

Load the overall ranking CSV file generated by NOREVA's assessment functions into R. Apply the norvisualization function with the cutoff parameter set to your desired rank threshold (e.g., cutoff='100' for top-100 workflows). The function extracts workflows ranked up to that cutoff, retrieves their corresponding performance metrics from the CSV, and generates a circular barplot in which bar radius represents the performance score and angular position reflects the ranking order. Render the result using R graphics functions and save as PNG or PDF format with a descriptive filename (e.g., NOREVA-Ranking-Top.100.workflows). The circular layout maximizes screen and print space compared to linear ranking plots when N is large.

## Related tools

- **norvisualization** (Primary R function that accepts the ranking CSV and cutoff parameter and generates the circular barplot structure and data transformation) — https://github.com/idrblab/NOREVA
- **R** (Statistical and graphics environment required to execute norvisualization and render output figures) — https://www.r-project.org/
- **ggord** (Installed dependency used for circular ordination and layout geometry in visualization) — https://github.com/fawda123/ggord

## Examples

```
norvisualization(fileName='overall_ranking.csv', cutoff='100')
```

## Evaluation signals

- Output file exists in expected format (PNG or PDF) with descriptive filename (e.g., NOREVA-Ranking-Top.100.workflows.*)
- Circular barplot displays exactly N bars where N matches the cutoff parameter; bar counts are auditable against the input CSV.
- Bar heights (radii) are monotonically non-increasing from rank 1 to rank N, reflecting the ranking order from the CSV.
- All workflows in the top-N subset of the ranking CSV are present in the figure; no workflows are missing or duplicated.
- Figure is legible and labels (workflow identifiers or abbreviations, performance scores, rank tick marks) are clearly visible without overlap when rendered at intended dimensions (typically 8–12 inches width for publication).

## Limitations

- Circular layout becomes crowded and difficult to label when N > 200–300; consider smaller cutoff or multiple stratified figures.
- Performance metric display is limited to the single score per workflow in the CSV; additional dimensions (e.g., sensitivity vs. specificity trade-offs) require supplementary materials.
- Requires pre-computed ranking CSV file; cannot rank workflows directly from raw peak tables or assessment results—must run assessment function first.
- No built-in statistical uncertainty or confidence interval display on bars; performance rankings are deterministic point estimates from the assessment criteria.

## Evidence

- [other] The norvisualization function accepts an overall ranking CSV file and a cutoff parameter set to '100' to produce a circular barplot illustration of the top-100 processing workflows ranked by performance.: "The norvisualization function accepts an overall ranking CSV file and a cutoff parameter set to "100" to produce a circular barplot illustration of the top-100 processing workflows ranked by"
- [readme] NOREVA enables high-throughput discovery and ranking of preprocessing workflows across multiple assessment criteria.: "The NOREVA package not only enables the pre-processing and assessment of multi-class/time-series metabolomic data but also realize a high-throughput discovery of the well-performing pre-processing"
- [other] Step-by-step workflow includes loading ranking CSV, applying norvisualization, generating circular layout, and saving output.: "1. Load the overall ranking CSV file containing workflow performance scores into R. 2. Apply norvisualization function to extract and prepare the top-100 ranked workflows with their corresponding"
- [readme] Five independent assessment criteria are integrated to rank workflows comprehensively.: "five well-established criteria, each with a distinct underlying theory, are integrated to ensure a much more comprehensive evaluation than any single criterion"