Abstract
Many studies assumed gene expression to be normally distributed. However, some were found to have left-skewed distribution, while others have right-skewed distribution. Here, we investigated the gene expression distribution of five lung adenocarcinoma data sets. We assumed that samples in the tail and non-tail of a skewed distribution were drawn from different populations with different survival outcomes. To investigate this hypothesis, skewed genes were detected to build a tail indicator matrix comprising of binary values. Survival analysis revealed that patients with more skewed genes in their tails had worse survival. Hierarchical clustering of the tail indicator matrices discovered a gene set with similar tail configurations for either left or right skewed genes. The two gene sets divided patients into three groups with different survivals. In conclusion, there is a direct association between genes with skewed distribution and the prognosis of lung adenocarcinoma patients.
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Acknowledgments
This work was supported by the Zhi-Yuan chair professorship start-up grant (WF220103010) from Shanghai Jiao Tong University.
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Chen, Y., Tu, S., Xu, L. (2017). The Prognostic Role of Genes with Skewed Expression Distribution in Lung Adenocarcinoma. In: Sun, Y., Lu, H., Zhang, L., Yang, J., Huang, H. (eds) Intelligence Science and Big Data Engineering. IScIDE 2017. Lecture Notes in Computer Science(), vol 10559. Springer, Cham. https://doi.org/10.1007/978-3-319-67777-4_57
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DOI: https://doi.org/10.1007/978-3-319-67777-4_57
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