Total Proteomics Differential Expression

Installation

⬇️ Click here to install in Cauldron (requires Cauldron to be running)

Repository: https://github.com/noatgnu/total-proteomics-differential-expression-plugin

Manual installation:

1. Open Cauldron
2. Go to Plugins → Install from Repository
3. Paste: https://github.com/noatgnu/total-proteomics-differential-expression-plugin
4. Click Install

ID: total-proteomics-differential-expression
Version: 1.0.0
Category: analysis
Author: CauldronGO Team

Description

Group-wise or Perseus-default imputation and limma differential expression for normalised total proteomics data

Workflow Diagram

flowchart TD
    Start([Start]) --> step1
    step1["Loading normalised matrix"]
    step1 --> step2
    step2["Loading annotation file"]
    step2 --> step3
    step3["Loading comparison file"]
    step3 --> step4
    step4["Imputing missing values"]
    step4 --> step5
    step5{"Running PCA (requires no missing values remaining)"}
    step5 --> step6
    step6["Fitting limma design"]
    step6 --> step7
    step7["Running differential expression comparisons"]
    step7 --> step8
    step8{"Generating target gene marker panels (requires target genes)"}
    step8 --> step9
    step9["Writing curtain exports"]
    step9 --> step10
    step10["Differential expression complete"]
    step10 --> End([End])

Runtime

• Environments: r

• Entrypoint: total_proteomics_differential_expression.R

Inputs

Input Details

Normalised Matrix File (normalized_matrix_file)

One of the QC & Normalisation plugin's normalized_.tsv outputs (Protein.Group, Genes, primary_gene, Category, then one column per sample)

Sample Annotation File (annotation_file)

Cauldron sample annotation file. Sample is matched against the matrix's sample columns by exact string, falling back to basename.

• Table Editor: Enabled with 3 columns
• Columns:
  • Sample: Sample (required)
  • Sample identifier matching a normalised-matrix column (full raw-file path or basename)
  • Condition: Condition (required)
  • Experimental group label
  • BioReplicate: BioReplicate
  • Biological replicate identifier (optional)

Comparison File (comparison_file)

Pairwise comparisons: columns condition_A, condition_B, comparison_label. Positive log2FC means condition_A > condition_B.

Imputation Method (impute_method)

'group_downshift' pools each Condition group's own samples to compute one mean/sd, then downshifts (group-wise, MNAR-aware). 'perseus_default' computes mean/sd separately for each sample column, matching Perseus's own default mode. 'none' leaves missing values as-is.

• Options: none, group_downshift, perseus_default

Imputation Downshift (SD units) (impute_downshift)

How far below the observed mean to centre imputed values, in standard deviations. Perseus default: 1.8.

Imputation Width (SD units) (impute_width)

Width of the imputed-value distribution, as a fraction of the observed standard deviation. Perseus default: 0.3.

FDR Cutoff (fdr_cutoff)

Adjusted p-value (BH) threshold for significance

Log2 Fold Change Threshold (fc_threshold_log2)

Minimum |log2 fold change| for significance (default 0.585 = log2(1.5))

Target Genes (comma-separated) (target_genes)

Optional gene symbols always labelled on every volcano plot and given their own marker abundance panel, regardless of significance. Leave empty to skip marker panels.

Top Genes per Direction (top_n_genes)

Number of top up- and down-regulated genes shown in the per-comparison top-genes bar chart

Outputs

Requirements

• R Version: >=4.0

R Dependencies (External File)

Dependencies are defined in: r-packages.txt

• SummarizedExperiment
• limma
• tidyverse
• ggplot2
• ggrepel
• patchwork
• pheatmap
• svglite
• scales
• writexl

Note: When you create a custom environment for this plugin, these dependencies will be automatically installed.

Example Data

This plugin includes example data for testing:

  annotation_file: examples/annotation.txt
  comparison_file: examples/comparison.txt
  impute_method: group_downshift
  normalized_matrix_file: examples/normalized_matrix.tsv

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

Usage

Via UI

1. Navigate to analysis → Total Proteomics Differential Expression
2. Fill in the required inputs
3. Click Run Analysis

Via Plugin System

const jobId = await pluginService.executePlugin('total-proteomics-differential-expression', {
  // Add parameters here
});