Why do pathway methods work better than they should?
Pathway analysis methods are frequently applied to cancer gene expression data to identify dysregulated pathways. These methods often infer pathway activity based on the expression of genes belonging to a given pathway, even though the proteins ultimately determine the activity of a given pathway. F...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
14 December 2020
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| In: |
FEBS letters
Year: 2020, Volume: 594, Issue: 24, Pages: 4189-4200 |
| ISSN: | 1873-3468 |
| DOI: | 10.1002/1873-3468.14011 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/1873-3468.14011 Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/1873-3468.14011 
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| Author Notes: | Bence Szalai and Julio Saez-Rodriguez |
MARC
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| 520 | |a Pathway analysis methods are frequently applied to cancer gene expression data to identify dysregulated pathways. These methods often infer pathway activity based on the expression of genes belonging to a given pathway, even though the proteins ultimately determine the activity of a given pathway. Furthermore, the association between gene expression levels and protein activities is not well-characterized. Here, we posit that pathway-based methods are effective not because of the correlation between expression and activity of members of a given pathway, but because pathway gene sets overlap with the genes regulated by transcription factors (TFs). Thus, pathway-based methods do not inform about the activity of the pathway of interest but rather reflect changes in TF activities. | ||
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