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Average fold-change of genetic pathways in biological transitions
Sandra Costa1, Joan Nieves1, Augusto Gonzalez1
1Institute of Cybernetics, Mathematics and Physics, Havana, 10400, Cuba.
Background:
A biological transition from a state N to a state T is marked by a rearrangement of the gene expression profile in the system, quantitatively measured through the differential expression of genes. In contrast, changes in genetic pathways are usually evaluated by means of hypothesis testing schemes.
Method:
A quantitative measure is introduced for the average fold-change of genetic pathways in a biological transition. We define the average fold-change of genes in each pathway and compare it with the average fold change of all genes in the transition. Python routines, able to process user-provided expression data and pathways databases, are created and deposited in a GitHub repository.
Results:
We apply the methodology to the characterization, in general terms, of the transition from a normal tissue to a tumor in 15 tumor localizations. Additionally, we study in more detail the transformation from primary to metastatic melanoma. Gene expression data from The Cancer Genome Atlas (TCGA) portal and the Reactome compilation of pathways are used for this purpose.
Conclusions:
The introduced average fold-change of genetic pathways in biological transitions is independent of assumptions inherent in hypothesis-testing approaches, enables quantitative comparisons between different biological transitions and, potentially provides a robust framework for tumor taxonomy or, in general, clustering of samples.
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