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The Prognostic Role of Genes with Skewed Expression Distribution in Lung Adenocarcinoma

  • Yajing Chen
  • Shikui Tu
  • Lei XuEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10559)

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.

Keywords

Skewed distribution Gene expression RNA-sequencing Microarray Survival Lung adenocarcinoma 

Notes

Acknowledgments

This work was supported by the Zhi-Yuan chair professorship start-up grant (WF220103010) from Shanghai Jiao Tong University.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Center for Cognitive Machines and Computational Health, and Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Department of Computer Science and EngineeringThe Chinese University of Hong KongHong Kong SARChina

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