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pyPAGE: Revaling Regulatory Mechanisms in Gene Expression through Unbiased Gene-set Enrichment Analysis
Understanding the regulatory mechanisms driving changes in gene expression is fundamental to systems biology. Our tool, pyPAGE, provides an unbiased method for identifying patterns of transcriptional and post-transcriptional regulation within specific cellular contexts. Applying pyPAGE to Alzheimer's disease bulk RNA sequencing data, we uncovered several novel regulators whose altered activity is significantly linked to the disease. Comprehensive analysis of additional single-cell and spatial sequencing data further confirms robustness of these patterns.Bakulin et al
Image Credit: Chiara Ricci-Tam, Scientific Design Strategist at Arc
Citation: (2024) PLoS Computational Biology Issue Image | Vol. 20(9) October 2024. PLoS Comput Biol 20(9): ev20.i09. https://doi.org/10.1371/image.pcbi.v20.i09
Published: October 7, 2024
Copyright: © 2024 . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Understanding the regulatory mechanisms driving changes in gene expression is fundamental to systems biology. Our tool, pyPAGE, provides an unbiased method for identifying patterns of transcriptional and post-transcriptional regulation within specific cellular contexts. Applying pyPAGE to Alzheimer's disease bulk RNA sequencing data, we uncovered several novel regulators whose altered activity is significantly linked to the disease. Comprehensive analysis of additional single-cell and spatial sequencing data further confirms robustness of these patterns.Bakulin et al
Image Credit: Chiara Ricci-Tam, Scientific Design Strategist at Arc