Biosaur 2.0.3

Proteomics post-search algorithm

Biosaur

Modern software for data analysis
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Table of Contents

• About the Project
  • Built With
• Getting Started
  • Installation
• Usage
• Targeted Mode
• Roadmap
• Contributing
• License
• Contact
• Acknowledgements

About The Project

Biosaur: open source peptide MS feature detector.

Biosaur provides the opportunity to work with:

• Data captured in negative mode
• Data containing information about ion mobility
• Also biosaurreports the correlation map

Biosaur algorithm allows users to get all the functionality of standard isotope detecting tool with the additional ability to analyze ion mobility data from devices of different types (such as FIAMS TimsTOF)

Built With

Biosaurus was developed using

• python3
• numpy
• pandas

Getting Started

Biosaur is a console utility that is easy to install and configure on your personal computer or computing cluster.

Installation

There are several options to install Biosaur.

• Easy way: you can use

pip3 install biosaur 

which inastall stable version of biosaur on your computer.

• If you want to get latest actual version of biosaur you shold use next algorithm:

1. Clone the repo

git clone https://github.com/abdrakhimov1/Biosaur.git

3. Enter the biosaur directory

cd Biosaur

4. Install biosaur:

pip3 insatall .

Usage

Biosaur is quite easy to use. To start your first bioasur search use command:

biosaur YOUR_FILE.mzML

This command will start standart biosaur search with default parameters. If you need to specify parameters use biosaur --help to identify the required parameter.

Special attention to TIMS TOF data.

First of all, the .d files should be converted to mzML format using msconvert with option '--combineIonMobilitySpectra'.

Please, do not use option --filter "scanSumming"! The latter is often required for MS/MS data analysis but breaks MS1 feature detection.

The best way to deal with it is to use --combineIonMobilitySpectra with --filter "msLevel 1" to create an individual mzML file for Biosaur-only analysis. At the current moment, TIMS TOF data has enormous size of files, as well as a huge amount of peaks, so it is highly recommended to use Biosaur --min_intensity option to reduce complexity of the analysis. For example, using --min_intensity 1000 option requires ~10 Gb of RAM memory and 20 mins of processing time on average PC (Intel i7-3930K CPU) when applied to a complex sample dataset containing 8000 MS1 spectra (200ng_HeLa_50cm_120min_100ms from PXD010012 on the ProteomeXchange). The same data with --min_intensity 800 filter requires 40 minutes of processing. The analyis of similar data for Orbitrap HF with no ion mobility info and no restrictions on --min_intensity takes ~5-10 min. In general, increasing --min_intensity reduces Biosaur analysis time and RAM consumption in non-linear way, but at the same time decreases sensitivity of feature detection.

Targeted Mode

Biosaur has targeted mode, in which it matches the results of identification of MS/MS spectra to the peptide features. To activate it, the MS/MS search results in pepXML or mzID format are required. Biosaur will take into account MS/MS search results during feature detection workflow. If you want to activate biosaur targeted mode, add a keyword --pxfp and provide path to the results of the MS/MS search engine.

Current Biosaur version supports X!Tandem, IdentiPy, MSFragger, Comet search outputs in pepXML formats, as well as MSGF+ output in mzID format.

Example:

biosaur YOUR_FILE.mzML --pxfp YOUR_SEARCH_ENGINE_RESULT.pep.xml

The output of Biosaur will contain a column with the MS/MS scans IDs and the corresponding peptide features, as in the standart mode of the Biosaur.

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

We are open and welcome various collaborations with representatives of the international community so we are ready to discuss any improvements to the biosaur. Any contributions you make are greatly appreciated. To help us with biosaur improvment follow next steps.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request
6. Contact us for discussion

License

Distributed under the Apache 2.0 License. See LICENSE for more information.

Contact

• Abdrakhimov Daniil - @abdrakhimov1 - [e-mail]
• Ivanov Mark - @markmipt - [e-mail]

Project Link: https://github.com/abdrakhimov1/Biosaur