A resampling-based meta-analysis for detection of differential gene expression in breast cancer


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Gur-Dedeoglu B., KONU KARAKAYALI Ö., Kir S., Ozturk A. R., Bozkurt B., Ergul G., ...More

BMC CANCER, vol.8, 2008 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 8
  • Publication Date: 2008
  • Doi Number: 10.1186/1471-2407-8-396
  • Journal Name: BMC CANCER
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Ankara University Affiliated: No

Abstract

Background: Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures.