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Testing Differential Gene Networks under Nonparanormal Graphical Models with False Discovery Rate Control
The nonparanormal graphical model has emerged as an important tool for modeling dependency structure between variables because it is flexible to non-Gaussian data while maintaining the good interpretability and computational convenience of Gaussian graphical models. In this paper, we consider the pr...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073847/ https://www.ncbi.nlm.nih.gov/pubmed/32033447 http://dx.doi.org/10.3390/genes11020167 |