https://github.com/cmkobel/ionquant

A label free quantification tool.

https://github.com/cmkobel/ionquant

Repository

A label free quantification tool.

https://github.com/cmkobel/IonQuant/blob/master/

IonQuant is a fast and comprehensive tool for MS1 precursor intensity-based quantification for timsTOF PASEF DDA and non-timsTOF (e.g., Orbitrap) data. It enables label-free quantification with false discovery (FDR) controlled match-between-runs (MBR). It can also be used for quantification in labelling-based experiments such as those involving SILAC, dimethyl, or similar labelling strategies. IonQuant is available as part of [FragPipe](http://fragpipe.nesvilab.org/) (recommended option), but can also be run as a command-line tool.  

### Workflow of peak tracing and quantification


### Workflow of FDR-controlled MBR


## It is fast


## It is accurate and sensitive

### Quantification accuracy evaluation using the three-organism dataset


### Quantified proteins and coefficient of variation (CV)


## System requirements
1. Java 1.8+.
2. `ext` folder from [MSFragger 3.4](https://msfragger.arsci.com/upgrader/).

**Note:** Bruker's native library needs [Visual C++ Redistributable for Visual Studio 2017](https://aka.ms/vs/16/release/VC_redist.x64.exe) in Windows. If you see an error saying cannot find Bruker native library, please try to install the Visual C++ redistibutable.

## Download
The latest IonQuant standalone JAR can be downloaded from [here](https://github.com/Nesvilab/IonQuant/releases/download/1.7.17/IonQuant-1.7.17.jar).

## Usage
### GUI
1. Download [FragPipe](http://fragpipe.nesvilab.org/) from [here](https://github.com/Nesvilab/FragPipe/releases/latest).
2. Follow the [tutorial](https://fragpipe.nesvilab.org/docs/tutorial_lfq.html).

#### Tutorials:
- [Using FragPipe coupled with MSFragger and IonQuant to analyze samples](https://fragpipe.nesvilab.org/docs/tutorial_fragpipe.html)
- [Analyzing SILAC (or other labelling coupled with MS1-based quantification) samples with FragPipe](https://fragpipe.nesvilab.org/docs/tutorial_silac.html)
- [Running MSstats using MSstats.csv from IonQuant](https://fragpipe.nesvilab.org/docs/tutorial_msstats.html)

### Command line
```shell
Usage:
        java -jar IonQuant.jar  --specdir  <.pepXML files>
        OR
        java -jar IonQuant.jar  --filelist 
Options:
        --specdir      # Directory containing the spectral files (d/mzml/mzxml/raw/quantindex). One --specdir indicates one spectral directory and can have multiple --specdir.
        --threads     # Number of threads. 0 = all logical cores. Default: 0
        --mztol         # MS1 tolerance in PPM. Default: 10.0
        --imtol         # 1/K0 tolerance. Default: 0.05
        --rttol         # Retention time tolerance. Unit: min. Default: 0.4
        --seedmz 0/1           # M/Z used as the start point of tracing. 0 = calculated M/Z; 1 = observed M/Z. Default: 0
        --psm          # Path to Philosopher's psm.tsv. One --psm indicates one psm.tsv and can have multiple --psm. Optional. Default: 
        --multidir     # Output directory for the multi-experimental result. Optional. Default: 
        --normalization 0/1    # Normalize the intensities across all runs. Default: 1
        --minisotopes 1/2/3    # Minimum isotopes required in feature extraction. Default: 2
        --minscans    # Minimum MS1 scans required in feature extraction. Default: 3
        --minions     # Minimum ions required in quantifying proteins. Only for MaxLFQ intensity. Default: 2
        --excludemods  # Excluded modifications in quantifying peptide sequences and proteins. Format: ;... Default: 
        --maxlfq 0/1           # Use MaxLFQ algorithm to calculate intensities. 0 = no, 1 = yes. Default: 1
        --minexps         # Minimum experiments in picking an ion for quantifying proteins. Only for intensity, not for MaxLFQ intensity. Default: 2
        --minfreq       # Minimum required frequency of an ion being selected for protein quantification. Only for intensity, not for MaxLFQ intensity. Default: 0.5
        --tp              # Number of ions used in quantifying each protein. If 0, using all ions. For intensity, not for MaxLFQ intensity. Default: 3
        --mbr 0/1              # Perform match-between-runs. Default: 0
        --mbrrttol      # Retention time tolerance used in match-between-runs. Unit: min. Default: 1.0
        --mbrimtol      # 1/K0 tolerance used in match-between-runs. Default: 0.05
        --mbrtoprun   # Maximum number of donor runs for each acceptor run. Default: 100000
        --mbrmincorr    # Minimum correlation coefficient between a donor run and its acceptor run. Default: 0
        --ionmobility 0/1      # The data has ion mobility information or not (for conventional LC-MS data). Default: 0
        --ionfdr        # Transferred ion false discovery rate threshold. Default: 0.01
        --peptidefdr    # Transferred peptide false discovery rate threshold. Default: 1
        --proteinfdr    # Transferred protein false discovery rate threshold. Default: 1
        --light        # Light labelling mass. Format: ;;... Optional. Default: 
        --medium       # Medium labelling mass. Format: ;;... Optional. Default: 
        --heavy        # Heavy labelling mass. Format: ;;... Optional. Default: 
        --requantify 0/1       # Re-quantify unidentified feature based on identified feature. Only activate when --light, --medium, or --heavy is not empty. Default: 1
        --writeindex 0/1       # Write indexed file on disk for further usage. 0 = no, 1 = yes. Default: 0
        --locprob       # Localization probability threshold. Default: 0
        --filelist     # A file list file containing --specdir, --psm, and --pepxml. Default: 
```
**Note:** in some high-performance computing (HPC) servers, you may need to explicitly specify `--threads ` in case that Java cannot correctly get the logical core number.

## Publications
Fast quantitative analysis of timsTOF PASEF data with MSFragger and IonQuant


Fengchao Yu, Sarah E. Haynes, Guo Ci Teo, Dmitry M. Avtonomov, Daniel A. Polasky, Alexey I. Nesvizhskii


Molecular & Cellular Proteomics, 19 (2020), 1575-1585, DOI: 10.1074/mcp.TIR120.002048

IonQuant Enables Accurate and Sensitive Label-Free Quantification With FDR-Controlled Match-Between-Runs


Fengchao Yu, Sarah E. Haynes, Alexey I. Nesvizhskii


Molecular & Cellular Proteomics, 20 (2021), 100077, DOI: 10.1016/j.mcpro.2021.100077

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