Proteomic Ruler

Version: 0.1.0

Commit Hash: b6dc958f6d227d91f09fe3f71178cf5c48f99866

Author: Toan Phung

Category: analysis

Subcategory: quantification

Estimate protein copy numbers and concentrations from deep profile mass spectrometry experiments using the Proteomic Ruler algorithm. Calculates copy numbers per cell, concentrations (nM), mass fractions, and mole fractions without spike-in standards. Based on: Wiśniewski et al. (2014) Mol Cell Proteomics 13:3497-3506. Implementation: https://github.com/noatgnu/proteomicRuler

Install with Cauldron get_app
README

Proteomic Ruler

Installation

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

Repository: https://github.com/noatgnu/proteomic-ruler-plugin

Manual installation:

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

ID: proteomic-ruler
Version: 0.1.0
Category: analysis
Author: Toan Phung

Description

Estimate protein copy numbers and concentrations from deep profile mass spectrometry experiments using the Proteomic Ruler algorithm. Calculates copy numbers per cell, concentrations (nM), mass fractions, and mole fractions without spike-in standards. Based on: Wiśniewski et al. (2014) Mol Cell Proteomics 13:3497-3506. Implementation: https://github.com/noatgnu/proteomicRuler

Runtime

  • Environments: python

  • Entrypoint: ruler.py

Inputs

Name Label Type Required Default Visibility
input_file Input Protein Intensities File file Yes - Always visible
accession_id_col Accession ID Column Name text Yes Protein.Ids Always visible
mw_column Molecular Weight Column Name text No Always visible
intensity_columns Intensity Columns column-selector (multiple) No - Always visible
ploidy Ploidy Number number (min: 1, max: 8, step: 1) Yes 2 Always visible
total_cellular Total Cellular Protein Concentration (pg/pL) number (min: 50, max: 500, step: 10) Yes 200 Always visible
get_mw Fetch Molecular Weight from UniProt boolean No false Always visible

Input Details

Input Protein Intensities File (input_file)

Tab-separated or CSV file containing protein intensities and UniProt accession IDs

Accession ID Column Name (accession_id_col)

Column name containing UniProt accession IDs (e.g., Protein.Ids, Majority protein IDs)

  • Placeholder: Protein.Ids

Molecular Weight Column Name (mw_column)

Column name containing molecular weight in kDa or Da (leave empty to fetch from UniProt)

  • Placeholder: Mass

Intensity Columns (intensity_columns)

Select intensity columns for samples. If empty, auto-detects columns matching 'Intensity*' pattern

Ploidy Number (ploidy)

Ploidy of the organism (1=haploid, 2=diploid, 3=triploid, etc.)

Total Cellular Protein Concentration (pg/pL) (total_cellular)

Total cellular protein concentration in picograms per picoliter (typical: 200 pg/pL)

Fetch Molecular Weight from UniProt (get_mw)

Automatically fetch molecular weights from UniProt if not present in input file (requires internet connection)

Outputs

Name File Type Format Description
ruler_output ruler_output.txt data txt Proteomic Ruler results with copy numbers, concentrations, and rankings

Requirements

  • Python Version: >=3.11

Python Dependencies (External File)

Dependencies are defined in: requirements.txt

  • proteomicruler>=0.1.6
  • pandas>=2.2.0
  • scipy>=1.11.0
  • seaborn>=0.13.0
  • uniprotparser>=1.2.0
  • click>=8.1.0
  • matplotlib>=3.7.0

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:

  input_file: diann/Reports.pg_matrix.tsv
  accession_id_col: Protein.Ids
  mw_column: 
  intensity_columns: [C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-IP_01.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-IP_02.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-IP_03.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-MockIP_01.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-MockIP_02.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-MockIP_03.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-IP_01.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-IP_02.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-IP_03.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-MockIP_01.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-MockIP_02.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-MockIP_03.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-WCL_01.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-WCL_02.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_BCA_LT-WCL_03.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-WCL_01.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-WCL_02.raw C:\Raja\DIA-NN searches\June 2022\LT-CBQCA-Test_DIA\RN-DS_220106_Pepide-CBQCA_LT-WCL_03.raw]
  ploidy: 2
  total_cellular: 200
  get_mw: true

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

Usage

Via UI

  1. Navigate to analysis → Proteomic Ruler
  2. Fill in the required inputs
  3. Click Run Analysis

Via Plugin System

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