title: A network-based method to evaluate quality of reproducibility of differential expression in cancer genomics studies.
abstract: BACKGROUND
  Personalized cancer treatments depend on the determination of a patient's genetic status according to known genetic profiles for which targeted treatments exist. Such genetic profiles must be scientifically validated before they is applied to general patient population. Reproducibility of findings that support such genetic profiles is a fundamental challenge in validation studies. The percentage of overlapping genes (POG) criterion and derivative methods produce unstable and misleading results. Furthermore, in a complex disease, comparisons between different tumor subtypes can produce high POG scores that do not capture the consistencies in the functions.
  
  
  RESULTS
  We focused on the quality rather than the quantity of the overlapping genes. We defined the rank value of each gene according to importance or quality by PageRank on basis of a particular topological structure. Then, we used the p-value of the rank-sum of the overlapping genes (PRSOG) to evaluate the quality of reproducibility. Though the POG scores were low in different studies of the same disease, the PRSOG was statistically significant, which suggests that sets of differentially expressed genes might be highly reproducible.
  
  
  CONCLUSIONS
  Evaluations of eight datasets from breast cancer, lung cancer and four other disorders indicate that quality-based PRSOG method performs better than a quantity-based method. Our analysis of the components of the sets of overlapping genes supports the utility of the PRSOG method.
authors.affiliation: Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.|State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, China.
authors.forename: Robin
authors.initials: R
authors.lastname: Li
authors.affiliation: Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Lin
authors.affiliation: Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
authors.forename: Haijiang
authors.initials: H
authors.lastname: Geng
authors.affiliation: Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
authors.forename: Zhihui
authors.initials: Z
authors.lastname: Li
authors.affiliation: Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
authors.forename: Jiabing
authors.initials: J
authors.lastname: Li
authors.affiliation: Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.|State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Lu
authors.affiliation: Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.|State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, Jiangsu, China.
authors.forename: Fangrong
authors.initials: F
authors.lastname: Yan
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D019295:Computational Biology; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease; D023281:Genomics / Q000379:methods* / Q000592:standards; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000473:pathology; D008297:Male; D011786:Quality Control; D015203:Reproducibility of Results
chemical_list: D014408:Biomarkers, Tumor
keywords: cancer genomics; gene expression; overlapping genes; pagerank; reproducibility