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CAMO: A molecular congruence analysis framework for evaluating model organisms

Year: 2021
Type: preprint
Abstract: ABSTRACT CAMO provides a rigorous and user-friendly solution for quantification and mechanistic exploration of omics congruence in model organisms and humans. It performs threshold-free differential analysis, quantitative concordance/discordance scoring, pathway-centric investigation, and topological subnetwork detection. Instead of dichotomous claims of “poorly” or “greatly” mimicking humans, CAMO facilitates discovery and visualization of specific molecular mechanisms that are best or least mimicked, providing foundations for hypothesis generation and subsequent translational investigations.
DOI: 10.1101/2021.11.21.469371
Authors: Wei Zong, Tanbin Rahman, Li Zhu, Xiangrui Zeng, Yingjin Zhang, Jian Zou, Song Liu, Zhao Ren, Jingyi Jessica Li, Steffi Osterreich, Tianzhou Ma, George C. Tseng
Institutions: University of Pittsburgh, The University of Texas MD Anderson Cancer Center, Carnegie Mellon University, Qilu University of Technology, University of California, Los Angeles, Magee-Womens Research Institute, University of Maryland, College Park
Language: English
Open Access status: green
OpenAlex ID: W3215105398
Cites: 37
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Related to: 10