Recent changes to Home

Home modified by Dinko Soic

Dinko Soic — Wed, 18 Mar 2026 13:58:37 -0000

--- v9
+++ v10
@@ -22,8 +22,8 @@


 - **Curated sugar database** with common, rare, and derivative monosaccharides, extensible with custom entries — see [Sugar Database](https://sourceforge.net/p/oxoniumbrowserx/wiki/Sugar%20Database/)
 - **Optional chemspace search** against >3,300 chemically plausible monosaccharide compositions for untargeted discovery of rare sugars — see [Sugar Database](https://sourceforge.net/p/oxoniumbrowserx/wiki/Sugar%20Database/)
-- **Built-in negative controls** using random test masses for empirical false discovery assessment — see [Detection Metrics](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20metrics/)
-- **Configurable detection parameters** including mass error tolerance, intensity threshold, and amino acid marker filtering — see [Detection Parameters](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20parameters/)
+- **Built-in negative controls** using random test masses for empirical false discovery assessment — see [Detection Metrics](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20Metrics/)
+- **Configurable detection parameters** including mass error tolerance, intensity threshold, and amino acid marker filtering — see [Detection Parameters](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20Parameters/)
 - **Interactive dashboard** with filtering, visualization, co-occurrence clustering, and export — see [Dashboard Guide](https://sourceforge.net/p/oxoniumbrowserx/wiki/Dashboard%20Guide/)

 ## Getting Started
@@ -50,8 +50,8 @@
 |------|-------------|
 | [System Architecture](https://sourceforge.net/p/oxoniumbrowserx/wiki/System%20Architecture/) | Pipeline architecture, module descriptions, data flow |
 | [Dashboard Guide](https://sourceforge.net/p/oxoniumbrowserx/wiki/Dashboard%20Guide/) | Walkthrough of each dashboard component |
-| [Detection Metrics](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20metrics/) | Understanding spectral counts, intensity, and presence |
-| [Detection Parameters](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20parameters/) | Configuring mass error, intensity threshold, and other settings |
+| [Detection Metrics](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20Metrics/) | Understanding spectral counts, intensity, and presence |
+| [Detection Parameters](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20Parameters/) | Configuring mass error, intensity threshold, and other settings |
 | [Sugar Database](https://sourceforge.net/p/oxoniumbrowserx/wiki/Sugar%20Database/) | Curated database, custom sugars, test masses, and chemspace search |

 ## Citation

Home modified by Dinko Soic

Dinko Soic — Wed, 18 Mar 2026 13:53:21 -0000

--- v8
+++ v9
@@ -1,146 +1,66 @@
-# Oxonium Browser Wiki Content
+# Oxonium Browser

-## Detailed System Overview
+## Overview

-The Oxonium Browser is designed to support untargeted glycopeptide discovery through sugar oxonium ion detection in high-resolution proteomics data. 
-Below is a comprehensive breakdown of each module, its function, and how they work together.
-Please note that the current beta version of the pipeline was developed using shotgun proteomics data from various Thermo Orbitrap mass spectrometers, including QE, Tribrid, and Astral.
-Raw data from other vendors have not yet been tested with the current beta version.
+The Oxonium Browser enables untargeted exploration of sugar oxonium ions in shotgun proteomics data, with a particular focus on prokaryotic protein glycosylation involving rare sugars. It scans high-resolution MS2 spectra for diagnostic oxonium ion pairs (intact ion + water loss fragment), filters out peptide spectra via a SAGE database search, and provides an interactive dashboard for exploring and exporting results.

-### System Architecture
+**Current version:** v1.1.0 (Beta)  
+**Developed using:** Thermo Orbitrap mass spectrometers (QE, Tribrid, Astral)  
+**Deployment:** Docker container with all dependencies included

-```
-┌───────────────┐     ┌───────────────┐     ┌───────────────┐     ┌───────────────┐
-│ SAGE Database │───▶│     mzML      │───▶ │  Oxonium Ion  │───▶│  Interactive  │
-│    Search     │     │  Calibration  │     │   Detection   │     │   Dashboard   │
-└───────────────┘     └───────────────┘     └───────────────┘     └───────────────┘
-```
+## How It Works

-## Data Flow and Processing
+1. **SAGE database search** removes MS2 spectra matching unmodified peptides
+2. **Two-pass mass recalibration** improves m/z accuracy using amino acid fragment reference peaks
+3. **Oxonium ion detection** scans remaining spectra for diagnostic sugar ion pairs within defined mass tolerance
+4. **Interactive dashboard** lets you filter, visualize, cluster, and export results
+5. **Excel reports** provide summary and detailed per-scan output

-### 1. **Input Phase:**

-   - mzML file containing MS2 spectra (must be pre-converted from RAW if necessary)
-   - FASTA database of protein sequences
-   - Excel file with oxonium ion definitions
+For the full technical pipeline documentation, see [System Architecture](https://sourceforge.net/p/oxoniumbrowserx/wiki/System%20Architecture/).

-### 2. **Processing Phase:**

-   - Perform SAGE database search to identify peptide spectra
-   - Read and recalibrate MS2 spectra
-   - Scan non-peptide spectra for sugar oxonium ions
-   - Process and visualize results
+## Key Features

-### 3. **Output Phase:**

-   - Generate summary Excel files
-   - Create detailed per-scan information
-   - Launch interactive dashboard for exploration
+- **Curated sugar database** with common, rare, and derivative monosaccharides, extensible with custom entries — see [Sugar Database](https://sourceforge.net/p/oxoniumbrowserx/wiki/Sugar%20Database/)
+- **Optional chemspace search** against >3,300 chemically plausible monosaccharide compositions for untargeted discovery of rare sugars — see [Sugar Database](https://sourceforge.net/p/oxoniumbrowserx/wiki/Sugar%20Database/)
+- **Built-in negative controls** using random test masses for empirical false discovery assessment — see [Detection Metrics](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20metrics/)
+- **Configurable detection parameters** including mass error tolerance, intensity threshold, and amino acid marker filtering — see [Detection Parameters](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20parameters/)
+- **Interactive dashboard** with filtering, visualization, co-occurrence clustering, and export — see [Dashboard Guide](https://sourceforge.net/p/oxoniumbrowserx/wiki/Dashboard%20Guide/)

-## Module Descriptions
+## Getting Started

-### 1. Pre-processing (External to Docker)
+### Requirements

-**Purpose:** Converting vendor-specific RAW files to open-format mzML files.
+- [Docker](https://www.docker.com/get-started) (version 19.03 or higher)
+- At least 4 GB RAM (more for Astral data)
+- At least 10 GB free disk space

-**Requirements:**
-- Must be performed by the user before running the Oxonium Browser
-- Recommended tool: ProteoWizard MSConvert
-- Preferred format: Centroided mzML with 64-bit encoding
+### Quick Start

-### 2. SAGE Database Search (`pysage_v6_scanner.py`)
+1. Download from [SourceForge](https://sourceforge.net/projects/oxoniumbrowserx/files/)
+2. Place your `.mzML`, `.fasta`, and the provided sugar database `.xlsx` in the `Input` directory
+3. Build: `docker build -t oxonium-browser .`
+4. Run: `docker run -it -p 8051:8051 -v "$(pwd)/Input:/app/Input" -v "$(pwd)/Output:/app/Output" oxonium-browser`
+5. Open http://localhost:8051

-**Purpose:** Identifies (unmodified) peptide fragmentation spectra to exclude from glycopeptide analysis.
+For full instructions including Windows commands and parameter customization, see the README file included in the download.

-**Key Features:**
-- Fast database peptide-spectrum matching
-- Target-decoy approach for FDR control
-- Supports static modifications (Carbamidomethylation C) and variable modifications (Oxidation M)
-- Returns matched scan numbers for filtering in downstream analysis
+## Wiki Pages

-### 3. mzML Calibration (`mzml_recalibration_v6.py`)
+| Page | Description |
+|------|-------------|
+| [System Architecture](https://sourceforge.net/p/oxoniumbrowserx/wiki/System%20Architecture/) | Pipeline architecture, module descriptions, data flow |
+| [Dashboard Guide](https://sourceforge.net/p/oxoniumbrowserx/wiki/Dashboard%20Guide/) | Walkthrough of each dashboard component |
+| [Detection Metrics](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20metrics/) | Understanding spectral counts, intensity, and presence |
+| [Detection Parameters](https://sourceforge.net/p/oxoniumbrowserx/wiki/Detection%20parameters/) | Configuring mass error, intensity threshold, and other settings |
+| [Sugar Database](https://sourceforge.net/p/oxoniumbrowserx/wiki/Sugar%20Database/) | Curated database, custom sugars, test masses, and chemspace search |

-**Purpose:** Reads mzML files and performs mass calibration for improved accuracy.
+## Citation

-**Key Features:**
-- Two-pass calibration approach:

-  1. Global linear calibration across all spectra
-  2. Per-spectrum linear calibration where sufficient reference peaks exist
-- Uses common amino acid fragments as reference masses
-- Generates diagnostic plots showing mass error improvement
+If you use this software in your research, please cite:

-### 4. Oxonium Ion Detection (`get_oxonium_scans_v3.py`)
+Soic D and Pabst M. NovoGlyco: mapping protein glycosylation in prokaryotes. *bioRxiv*. 2026.

-**Purpose:** Scans MS2 spectra for diagnostic sugar oxonium ions indicative of glycopeptides.
+## Contact

-**Key Features:**
-- Searches for pairs of diagnostic masses for each sugar 
-- Focuses only on spectra not identified as peptides in the database search
-- Calculates normalized intensity relative to total spectrum intensity
-- Generates comprehensive statistics on detection frequencies
-
-### 5. Results Processing (`process_results.py`)
-
-**Purpose:** Organizes raw detection results into structured, sorted datasets.
-
-**Key Features:**
-- Separates test ions from actual oxonium ions
-- Sorts results by normalized presence
-- Prepares data for visualization and export
-
-### 6. Interactive Dashboard (`ox_scanner_dash_v19.py`)
-
-**Purpose:** Provides an interactive visualization of detected oxonium ions.
-
-**Key Features:**
-- Multiple visualization types:

-  - Dual metric heatmaps (intensity vs. presence)
-  - Bubble charts showing distribution of detections
-  - Retention time profiles for selected ions
-  - Mass error distribution plots
-- Real-time filtering by intensity, presence, and count thresholds
-- Threshold optimization using test masses:
-  - Random test masses serve as built-in negative controls
-  - Real-time visual comparison between genuine oxonium ions and test masses
-  - Allows empirical determination of optimal filtering thresholds
-  - Helps distinguish true glycan signals from random matches
-  - For detailed guidance on interpreting metrics and optimizing thresholds, see [Detection Metrics](Detection metrics)
-
-  
-NOTE: Additionally, the Sage search file is saved in the input folder, while the oxonium ion detection results are saved as Excel files in the specified output folder.
-
-### 7. Main Script Orchestration (`main_script.py`)
-
-**Purpose:** Coordinates the entire workflow and handles parameter management.
-
-**Key Features:**
-- Environment variable integration for flexible configuration
-- Input/output file management
-- Pipeline orchestration and error handling
-- Dashboard launching
-
-### Important Considerations
-
-**Mass-Based Detection Limitations:**
-This approach identifies sugars based on diagnostic oxonium ion masses, but cannot differentiate between isomeric sugars. 
-For example, when a hexose (Hex) is detected, additional biochemical experiments or literature review would be required to determine whether it represents glucose, galactose, mannose, or another hexose isomer. 
-The tool provides evidence of glycosylation and sugar mass, but structural characterization requires complementary techniques.
-
-**File Format Requirements:**
-The Docker version requires pre-converted mzML files and does not support direct analysis of RAW files due to compatibility limitations with Windows-native libraries in Linux containers.
-
-##  Configuration
-
-### Mass Calibration Parameters
-- Reference peaks used: 147.11280, 175.11895, 201.12337, 215.13902, 228.1343, 258.1448, 292.1292
-- These masses correspond to common fragment ions in glycopeptide spectra
-- Default tolerance for initial matching: 20 ppm
-- Tighter tolerance for individual calibration: 10 ppm
-
-### Oxonium Ion Detection Parameters
-- MASS_ERROR: Maximum mass error for matching (default: 0.001 Da)
-- INTENSITY_THRESHOLD: Minimum normalized intensity (default: 0.25%)
-- AMINO_ACID_MARKER: Optional requirement for amino acid fragment ions
-
-### SAGE Search Parameters
-- Enzyme: Trypsin (KR, not before P)
-- Static modifications: Carbamidomethylation (C)
-- Variable modifications: Oxidation (M)
-- Default FDR threshold: 1%
+Dinko Soic — soic@imsb.biol.ethz.ch  
+Martin Pabst — m.pabst@tudelft.nl

Home modified by Dinko Soic

Dinko Soic — Thu, 29 May 2025 08:43:10 -0000

--- v7
+++ v8
@@ -85,7 +85,7 @@
 - Sorts results by normalized presence
 - Prepares data for visualization and export

-### 6. Interactive Dashboard (`ox_scanner_dash_v17.py`)
+### 6. Interactive Dashboard (`ox_scanner_dash_v19.py`)

 **Purpose:** Provides an interactive visualization of detected oxonium ions.

Home modified by Dinko Soic

Dinko Soic — Sun, 02 Mar 2025 20:48:07 -0000

--- v6
+++ v7
@@ -101,7 +101,7 @@
   - Real-time visual comparison between genuine oxonium ions and test masses
   - Allows empirical determination of optimal filtering thresholds
   - Helps distinguish true glycan signals from random matches
-  - For detailed guidance on interpreting metrics and optimizing thresholds, see [Detection Metrics](Detection Metrics)
+  - For detailed guidance on interpreting metrics and optimizing thresholds, see [Detection Metrics](Detection metrics)


 NOTE: Additionally, the Sage search file is saved in the input folder, while the oxonium ion detection results are saved as Excel files in the specified output folder.

Home modified by Dinko Soic

Dinko Soic — Sun, 02 Mar 2025 20:47:36 -0000

--- v5
+++ v6
@@ -101,7 +101,7 @@
   - Real-time visual comparison between genuine oxonium ions and test masses
   - Allows empirical determination of optimal filtering thresholds
   - Helps distinguish true glycan signals from random matches
-  - For detailed guidance on interpreting metrics and optimizing thresholds, see [Detection Metrics](Oxonium_Ion_Detection_Metrics)
+  - For detailed guidance on interpreting metrics and optimizing thresholds, see [Detection Metrics](Detection Metrics)


 NOTE: Additionally, the Sage search file is saved in the input folder, while the oxonium ion detection results are saved as Excel files in the specified output folder.

Home modified by Dinko Soic

Dinko Soic — Sun, 02 Mar 2025 20:45:28 -0000

--- v4
+++ v5
@@ -101,6 +101,8 @@
   - Real-time visual comparison between genuine oxonium ions and test masses
   - Allows empirical determination of optimal filtering thresholds
   - Helps distinguish true glycan signals from random matches
+  - For detailed guidance on interpreting metrics and optimizing thresholds, see [Detection Metrics](Oxonium_Ion_Detection_Metrics)
+

 NOTE: Additionally, the Sage search file is saved in the input folder, while the oxonium ion detection results are saved as Excel files in the specified output folder.

Home modified by Dinko Soic

Dinko Soic — Sun, 02 Mar 2025 20:34:22 -0000

--- v3
+++ v4
@@ -124,7 +124,7 @@
 **File Format Requirements:**
 The Docker version requires pre-converted mzML files and does not support direct analysis of RAW files due to compatibility limitations with Windows-native libraries in Linux containers.

-## Advanced Configuration
+##  Configuration

 ### Mass Calibration Parameters
 - Reference peaks used: 147.11280, 175.11895, 201.12337, 215.13902, 228.1343, 258.1448, 292.1292

Home modified by Dinko Soic

Dinko Soic — Sun, 02 Mar 2025 20:33:52 -0000

--- v2
+++ v3
@@ -18,18 +18,18 @@

 ## Data Flow and Processing

-1. **Input Phase:**
+### 1. **Input Phase:**
    - mzML file containing MS2 spectra (must be pre-converted from RAW if necessary)
    - FASTA database of protein sequences
    - Excel file with oxonium ion definitions

-2. **Processing Phase:**
+### 2. **Processing Phase:**
    - Perform SAGE database search to identify peptide spectra
    - Read and recalibrate MS2 spectra
    - Scan non-peptide spectra for sugar oxonium ions
    - Process and visualize results

-3. **Output Phase:**
+### 3. **Output Phase:**
    - Generate summary Excel files
    - Create detailed per-scan information
    - Launch interactive dashboard for exploration

Home modified by Dinko Soic

Dinko Soic — Sun, 02 Mar 2025 19:55:05 -0000

--- v1
+++ v2
@@ -1,8 +1,144 @@
-Welcome to your wiki!
+# Oxonium Browser Wiki Content

-This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].
+## Detailed System Overview

-The wiki uses [Markdown](/p/oxoniumbrowserx/wiki/markdown_syntax/) syntax.
+The Oxonium Browser is designed to support untargeted glycopeptide discovery through sugar oxonium ion detection in high-resolution proteomics data. 
+Below is a comprehensive breakdown of each module, its function, and how they work together.
+Please note that the current beta version of the pipeline was developed using shotgun proteomics data from various Thermo Orbitrap mass spectrometers, including QE, Tribrid, and Astral.
+Raw data from other vendors have not yet been tested with the current beta version.

-[[members limit=20]]
-[[download_button]]
+### System Architecture
+
+```
+┌───────────────┐     ┌───────────────┐     ┌───────────────┐     ┌───────────────┐
+│ SAGE Database │───▶│     mzML      │───▶ │  Oxonium Ion  │───▶│  Interactive  │
+│    Search     │     │  Calibration  │     │   Detection   │     │   Dashboard   │
+└───────────────┘     └───────────────┘     └───────────────┘     └───────────────┘
+```
+
+## Data Flow and Processing
+
+1. **Input Phase:**
+   - mzML file containing MS2 spectra (must be pre-converted from RAW if necessary)
+   - FASTA database of protein sequences
+   - Excel file with oxonium ion definitions
+
+2. **Processing Phase:**
+   - Perform SAGE database search to identify peptide spectra
+   - Read and recalibrate MS2 spectra
+   - Scan non-peptide spectra for sugar oxonium ions
+   - Process and visualize results
+
+3. **Output Phase:**
+   - Generate summary Excel files
+   - Create detailed per-scan information
+   - Launch interactive dashboard for exploration
+
+## Module Descriptions
+
+### 1. Pre-processing (External to Docker)
+
+**Purpose:** Converting vendor-specific RAW files to open-format mzML files.
+
+**Requirements:**
+- Must be performed by the user before running the Oxonium Browser
+- Recommended tool: ProteoWizard MSConvert
+- Preferred format: Centroided mzML with 64-bit encoding
+
+### 2. SAGE Database Search (`pysage_v6_scanner.py`)
+
+**Purpose:** Identifies (unmodified) peptide fragmentation spectra to exclude from glycopeptide analysis.
+
+**Key Features:**
+- Fast database peptide-spectrum matching
+- Target-decoy approach for FDR control
+- Supports static modifications (Carbamidomethylation C) and variable modifications (Oxidation M)
+- Returns matched scan numbers for filtering in downstream analysis
+
+### 3. mzML Calibration (`mzml_recalibration_v6.py`)
+
+**Purpose:** Reads mzML files and performs mass calibration for improved accuracy.
+
+**Key Features:**
+- Two-pass calibration approach:
+  1. Global linear calibration across all spectra
+  2. Per-spectrum linear calibration where sufficient reference peaks exist
+- Uses common amino acid fragments as reference masses
+- Generates diagnostic plots showing mass error improvement
+
+### 4. Oxonium Ion Detection (`get_oxonium_scans_v3.py`)
+
+**Purpose:** Scans MS2 spectra for diagnostic sugar oxonium ions indicative of glycopeptides.
+
+**Key Features:**
+- Searches for pairs of diagnostic masses for each sugar 
+- Focuses only on spectra not identified as peptides in the database search
+- Calculates normalized intensity relative to total spectrum intensity
+- Generates comprehensive statistics on detection frequencies
+
+### 5. Results Processing (`process_results.py`)
+
+**Purpose:** Organizes raw detection results into structured, sorted datasets.
+
+**Key Features:**
+- Separates test ions from actual oxonium ions
+- Sorts results by normalized presence
+- Prepares data for visualization and export
+
+### 6. Interactive Dashboard (`ox_scanner_dash_v17.py`)
+
+**Purpose:** Provides an interactive visualization of detected oxonium ions.
+
+**Key Features:**
+- Multiple visualization types:
+  - Dual metric heatmaps (intensity vs. presence)
+  - Bubble charts showing distribution of detections
+  - Retention time profiles for selected ions
+  - Mass error distribution plots
+- Real-time filtering by intensity, presence, and count thresholds
+- Threshold optimization using test masses:
+  - Random test masses serve as built-in negative controls
+  - Real-time visual comparison between genuine oxonium ions and test masses
+  - Allows empirical determination of optimal filtering thresholds
+  - Helps distinguish true glycan signals from random matches
+  
+NOTE: Additionally, the Sage search file is saved in the input folder, while the oxonium ion detection results are saved as Excel files in the specified output folder.
+
+### 7. Main Script Orchestration (`main_script.py`)
+
+**Purpose:** Coordinates the entire workflow and handles parameter management.
+
+**Key Features:**
+- Environment variable integration for flexible configuration
+- Input/output file management
+- Pipeline orchestration and error handling
+- Dashboard launching
+
+### Important Considerations
+
+**Mass-Based Detection Limitations:**
+This approach identifies sugars based on diagnostic oxonium ion masses, but cannot differentiate between isomeric sugars. 
+For example, when a hexose (Hex) is detected, additional biochemical experiments or literature review would be required to determine whether it represents glucose, galactose, mannose, or another hexose isomer. 
+The tool provides evidence of glycosylation and sugar mass, but structural characterization requires complementary techniques.
+
+**File Format Requirements:**
+The Docker version requires pre-converted mzML files and does not support direct analysis of RAW files due to compatibility limitations with Windows-native libraries in Linux containers.
+
+## Advanced Configuration
+
+### Mass Calibration Parameters
+- Reference peaks used: 147.11280, 175.11895, 201.12337, 215.13902, 228.1343, 258.1448, 292.1292
+- These masses correspond to common fragment ions in glycopeptide spectra
+- Default tolerance for initial matching: 20 ppm
+- Tighter tolerance for individual calibration: 10 ppm
+
+### Oxonium Ion Detection Parameters
+- MASS_ERROR: Maximum mass error for matching (default: 0.001 Da)
+- INTENSITY_THRESHOLD: Minimum normalized intensity (default: 0.25%)
+- AMINO_ACID_MARKER: Optional requirement for amino acid fragment ions
+
+### SAGE Search Parameters
+- Enzyme: Trypsin (KR, not before P)
+- Static modifications: Carbamidomethylation (C)
+- Variable modifications: Oxidation (M)
+- Default FDR threshold: 1%

Home modified by glycolab

glycolab — Sat, 08 Feb 2025 00:57:06 -0000

Welcome to your wiki!

This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].

The wiki uses Markdown syntax.

Project Members:

glycolab (admin)