Omics Untargeted Key Script (OUKS)

Brief Description 🗝️

R based open-source collection of scripts called 🔴OUKS🔵 (Omics Untargeted Key Script) providing comprehensive nine step LC-MS untargeted metabolomic profiling data processing toolbox 🧰

See website 💻

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Table of contents 📋

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• Instruction and introduction into the 🔴OUKS toolbox:large_blue_circle: are provided by Basic tutorial file. Session info and Used packages are listed in corresponding files.
• Scripts with comments, notes and references are stored in Scripts folder at a previously defined order along with code for plotting figures associated with article.
• MS2 spectra for selected potential biomarkers of bladder cancer are stored in mzXML format at corresponding folder.
• Datasets in .csv and other files (.RData, .R) are available for reproducibility from corresponding folders. Files descriptions are provived by Roadmap file. Raw data (.CDF format) are available from Metabolomics Workbench Repository, study ID: ST001682. Metadata table is also provided.
• Report in .Rmd, .pdf and .docx formats were provided as an example to reproduce the OUKS code script.
• Changelog file is provided and is constantly updated. See also releases page.
• Required packages is for storing packages archives with strong version dependency.
• Discussions, suggestions and error reports are welcome.

Script	Purpose
1. Randomization.R	experimental design and sample randomization
2. Integration.R	peaks integration and time alignment
3. Imputation.R	missing value imputation (MVI) and artifacts removal
4. Correction.R	signal drift correction and batch effect removal
5. Annotation.R	feature annotation and tentative identification by database search
6. Filtering.R	peaks filtering for quality checking and accounting of technical variation
7. Normalization.R	data normalization and adjusting of biological variation
8. Grouping.R	peaks grouping and molecular features clustering
9. Statistics.R	statistical analysis and hypothesis testing

Requirements 🏗️

The only requirements are to be familiar with the basic syntax of the R language, PC with Internet connection and Windows OS (desirable), RStudio and R (≥ 4.1.2).

Citation 🔗

OUKS has been published in the Journal of Proteome Research. If you use this software to analyze your own data, please cite it as below, thanks:

Ivan V. Plyushchenko, Elizaveta S. Fedorova, Natalia V. Potoldykova, Konstantin A. Polyakovskiy, Alexander I. Glukhov, and Igor A. Rodin Journal of Proteome Research 2022 21 (3), 833-847. DOI: 10.1021/acs.jproteome.1c00392

OUKS builds on many open-source software tools and open data sources. Therefore, it is important to also cite their work when using these algorithms via OUKS: 1, 2.

Contact 📝

Please send any comment, suggestion or question you may have to the author (👨‍🔬 Dr. Ivan Plyushchenko):