Published September 26, 2023
| Version v1
Software
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Code for: Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis
Creators
- 1. The School of Bioscience, University of Skövde and Department of Physics, Chemistry and Biology, Linköping University
- 2. Department of Biomedical and Clinical Sciences, Linköping University
Description
Code for performing data analyses of proteomics data from persons with multiple sclerosis (MS) and healthy controls. Protein levels were measured, using proximity-extension assay combined with next-generation sequencing (Olink Explore), in cerebrospinal fluid samples and plasma samples from persons with MS (n = 186) and healthy controls (n = 43). A machine learning approach were used to identify protein biomarkers which could predict diagnosis, disease activity and long-term disability outcomes in multiple sclerosis.
Files
Code.zip
Files
(56.8 kB)
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