Developing a novel test to detect cancer genes from microarray data

Shreya Mathur, Sunil Mathur

Research output: Contribution to journalArticlepeer-review


DNA microarray technology can simultaneously screen thousands of gene expression profiles, transforming how genetics is applied in medicine. However, the lack of normality in microarray data renders common statistical methods ineffective. We propose a novel statistical method which does not require stringent assumptions but is still more powerful than some of its competitors. Using both simulation studies and clinical data, we show that our novel method outperforms previous methods. The limiting distribution for the proposed test is obtained for under null and alternative hypotheses. The proposed test will help make cancer treatment and gene therapy more successful, and it may facilitate research regarding cancer vaccinations. The proposed test may also help in the development of a prediction model in genetic profiling studies built on a subset of differentially expressed genes and the clinical data to assess the accuracy of the clinical prediction.

Original languageEnglish (US)
Pages (from-to)628-646
Number of pages19
JournalInternational Journal of Bioinformatics Research and Applications
Issue number6
StatePublished - 2014


  • Data
  • Differentially expressed genes
  • Location
  • Power
  • Test
  • Type I error

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Clinical Biochemistry
  • Health Information Management


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