Coefficient of Variation Plot

Version: 1.0.0

Commit Hash: ac1d4888cd5a9be780159bc2a1e456469804a29c

Author: CauldronGO Team

Category: visualization

Generate coefficient of variation (CV) plots for DIA-NN data quality assessment

README

Coefficient of Variation Plot

ID: cv-plot
Version: 1.0.0
Category: visualization
Author: CauldronGO Team

Description

Generate coefficient of variation (CV) plots for DIA-NN data quality assessment

Runtime

  • Type: python
  • Script: cv.py

Inputs

Name Label Type Required Default Visibility
annotation_file Annotation File file Yes - Always visible
log_file_path Log File file No - Always visible
report_pr_file_path Protein Report File file No - Always visible
report_pg_file_path Protein Group Report File file No - Always visible
intensity_col Intensity Column text No Intensity Always visible
sample_names Sample Names text No - Always visible

Input Details

Annotation File (annotation_file)

Sample annotation file with conditions

Log File (log_file_path)

DIA-NN log file to extract sample names (optional if sample_names provided)

Protein Report File (report_pr_file_path)

DIA-NN protein-level report file

Protein Group Report File (report_pg_file_path)

DIA-NN protein group-level report file

Intensity Column (intensity_col)

Name of the intensity column in the report files

Sample Names (sample_names)

Comma-separated sample names (required if log file not provided)

  • Placeholder: Sample1,Sample2,Sample3

Outputs

Name File Type Format Description
pr_cv_plot pr_cv.svg image svg CV plot for protein-level data
pg_cv_plot pg_cv.svg image svg CV plot for protein group-level data

Requirements

  • Python: >=3.11
  • Packages:
  • pandas>=2.0.0
  • numpy>=1.24.0
  • scipy>=1.10.0
  • seaborn>=0.12.0
  • matplotlib>=3.7.0

Example Data

This plugin includes example data for testing:

  annotation_file: diann/annotation.txt
  log_file_path: diann/Reports.log.txt
  report_pr_file_path: diann/Reports.pr_matrix.tsv
  report_pg_file_path: diann/Reports.pg_matrix.tsv

Load example data by clicking the Load Example button in the UI.

Usage

Via UI

  1. Navigate to visualization → Coefficient of Variation Plot
  2. Fill in the required inputs
  3. Click Run Analysis

Via Plugin System

const jobId = await pluginService.executePlugin('cv-plot', {
  // Add parameters here
});