Applications of Bayesian Network Models in Predicting Types of Hematological Malignancies

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dc.contributor.authorAgrahari, Rupesh
dc.contributor.authorForoushani, Amir
dc.contributor.authorDocking, T. Roderick
dc.contributor.authorChang, Linda
dc.contributor.authorDuns, Gerben
dc.contributor.authorHudoba, Monika
dc.contributor.authorKarsan, Aly
dc.contributor.authorZare, Habil
dc.date.accessioned2019-08-27T13:00:49Z
dc.date.available2019-08-27T13:00:49Z
dc.date.issued2018-05
dc.description.abstractNetwork analysis is the preferred approach for the detection of subtle but coordinated changes in expression of an interacting and related set of genes. We introduce a novel method based on the analyses of coexpression networks and Bayesian networks, and we use this new method to classify two types of hematological malignancies; namely, acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). Our classifier has an accuracy of 93%, a precision of 98%, and a recall of 90% on the training dataset (n = 366); which outperforms the results reported by other scholars on the same dataset. Although our training dataset consists of microarray data, our model has a remarkable performance on the RNA-Seq test dataset (n = 74, accuracy = 89%, precision = 88%, recall = 98%), which confirms that eigengenes are robust with respect to expression profiling technology. These signatures are useful in classification and correctly predicting the diagnosis. They might also provide valuable information about the underlying biology of diseases. Our network analysis approach is generalizable and can be useful for classifying other diseases based on gene expression profiles. Our previously published <i>Pigengene</i> package is publicly available through Bioconductor, which can be used to conveniently fit a Bayesian network to gene expression data.
dc.description.departmentComputer Science
dc.formatText
dc.format.extent12 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationAgrahari, R., Foroushani, A., Docking, T. R., Chang, L., Duns, G., Hudoba, M., Karsan, A., & Zare, H. (2018). Applications of Bayesian network models in predicting types of hematological malignancies. Scientific Reports, 8(6951).
dc.identifier.doihttps://doi.org/10.1038/s41598-018-24758-5
dc.identifier.urihttps://hdl.handle.net/10877/8546
dc.language.isoen
dc.publisherNature Publishing Group
dc.rights.holder© 2018 The Author(s).
dc.rights.licenseThis work is licensed under a Creative Commons Attribution 4.0 International License.
dc.sourceScientific Reports, 2018, Vol. 8, Article 6951.
dc.subjectBayesian network models
dc.subjecthematological malignancies
dc.subjectgenes
dc.subjectComputer Science
dc.titleApplications of Bayesian Network Models in Predicting Types of Hematological Malignancies
dc.typeArticle

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