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Pathway level analysis by augmenting activities of transcription factor target genes

  • H. Jung
  • , E. Lee
  • , J. W. Kim
  • , D. Lee
  • University of California at San Diego
  • Korea Advanced Institute of Science and Technology
  • Sungkyunkwan University

Research output: Contribution to journalArticlepeer-review

Abstract

Many approaches to discovering significant pathways in gene expression profiles have been developed to facilitate biological interpretation and hypothesis generation. In this work, the authors propose a pathway identification scheme integrating the activity of pathway member genes with that of target genes of transcription factors (TFs) in the same pathway by the weighted Z-method. The authors evaluated the integrative scoring scheme in gene expression profiles of essential thrombocythemia patients with JAK2V617F mutation status, primary breast tumour samples with the status of metastasis occurrence, two independent lung cancer expression profiles with their prognosis, and found that our approach identified cancer-type-specific pathways better than gene set enrichment analysis (GSEA) and Tian's method using the original pathways [pathways that have TFs from database] and the extended pathways (including target genes of TFs of the original pathways). The success of our scheme implicates that adding information of transcriptional regulation is better way of utilising mRNA measurements for estimating differential activities of pathways from gene expression profiles more exactly.

Original languageEnglish
Article numberISBEAT000003000006000534000001
Pages (from-to)534-542
Number of pages9
JournalIET Systems Biology
Volume3
Issue number6
DOIs
StatePublished - Nov 2009
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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