The hypothesis of data probability density distributions has many effects on the design of a new statistical method. Based on the analysis of a group of real gene expression profiles, this study reveal that the primary density distributions of the real profiles are normal/log-normal and t distributions, accounting for 80% and 19% respectively. According to these distributions, we generated a series of simulation data to make a more comprehensive assessment for a novel statistical method, maximal information coefficient (MIC). The results show that MIC is not only in the top tier in the overall performance of identifying differentially expressed genes, but also exhibits a better adaptability and an excellent noise immunity in comparison with the existing methods.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Shanzhou Niu received his Ph.D. degree in biomedical engineering from Southern Medical University in 2015. Then he joined the School of Mathematics and Computer Science at the Gannan Normal University. He is currently a postdoctoral researcher in the Department of Radiation Oncology at UT Southwestern Medical Center. His research interests include CT imaging, image processing, and optimization theory and methods. You Zhang received his Ph.D. degree in biomedical engineering from Duke University in 2015. He is currently an assistant professor in the Department of Radiation Oncology at the UT Southwestern Medical Center. His research interests include CT/CBCT reconstruction and image registration. Yuncheng Zhong is currently an instructor in the Department of Radiation Oncology at the UT Southwestern Medical Center. His research interests include CT and PET imaging. Guoliang liu is currently an associated professor in the School of Information Engineering at the Gannan Medical Unviersity. His research interest is CT imaging. Shaohui Lu is currently an associated professor in the First Affiliated Hospital of Gannan Medical University. His research interesting is perfusion CT imaging.

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