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https://github.com/sysbiochalmers/gagome-mced


https://github.com/sysbiochalmers/gagome-mced

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README

          

# `GAGome-MCED`

## 🔬 Description

This repository contains code and example data sets for the publication "Noninvasive detection of any-stage cancer using free glycosaminoglycans".
Both a synthetic data set with standardized GAGome values and the code for the development of free GAGome MCED scores are available in the subfolders.

## 💻 Installation and usage

Run the Rmarkdown file Projpred_synth.Rmd in order to produce a model for predicting the probability of cancer using plasma and urine GAGomes as input data. A pre-knitted HTML report is also available if you are not interested in re-running the code yourself.

https://sysbiochalmers.github.io/GAGome-MCED/projpred_synth.html

## 📖 Publication

The free GAGome MCED scores are used in the publication below:
```
Noninvasive detection of any-stage cancer using free glycosaminoglycans
Sinisa Bratulic, Angelo Limeta, Saeed Dabestani, Helgi Birgisson, Gunilla Enblad, Karin Stålberg,
Göran Hesselager, Michael Häggman,Martin Höglund, Oscar E Simonson, Peter Stålberg, Henrik Lindman,
Anna BÃ¥ng-Rudenstam, Matias Ekstrand, Gunjan Kumar, Ilaria Cavarretta,Massimo Alfano, Francesco Pellegrino,
Thomas Mandel-Clausen, Ali Salanti, Francesca Maccari, Fabio Galeotti, Nicola Volpi, Mads Daugaard,
Mattias Belting, Sven Lundstam, Ulrika Stierner, Jan Nyman, Bengt Bergman, Per-Henrik Edqvist, Max Levin,
Andrea Salonia, Henrik Kjölhede, Eric Jonasch, Jens Nielsen, Francesco Gatto
Manuscript doi: 10.1073/pnas.2115328119
Manuscript link: https://www.pnas.org/doi/10.1073/pnas.2115328119
```

## 👋 Contact

Please reach out to our email with any comments, questions or concerns:

[Sinisa Bratulic](mailto:bratulic@chalmers.se)

[Angelo Limeta](mailto:angelol@chalmers.se)