AI Article Synopsis
- - The protocol focuses on analyzing the metabolic landscape of breast tumors to help classify patients based on their metabolic profiles.
- - It involves examining 1,454 metabolic genes tied to 90 pathways and utilizing an algorithm to determine the deregulation of these pathways in tumor samples.
- - The process includes clustering analysis to find metabolic subtypes and implementing machine learning to create distinct signatures for each subtype.
Article Abstract
Here, we present a protocol for analyzing the global metabolic landscape in breast tumors for the purpose of metabolism-based patient stratification. We describe steps for analyzing 1,454 metabolic genes representing 90 metabolic pathways and subjecting them to an algorithm that calculates the deregulation score of 90 pathways in each tumor sample, thus converting gene-level information into pathway-level information. We then detail procedures for performing clustering analysis to identify metabolic subtypes and using machine learning to develop a signature representing each subtype. For complete details on the use and execution of this protocol, please refer to Iqbal et al..
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11452911 | PMC |
| http://dx.doi.org/10.1016/j.xpro.2024.103173 | DOI Listing |
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