Integrated Center for Oncology

Breast Cancer Gene-Expression Miner v5.1
(bc-GenExMiner v5.1)

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Exhaustive prognostic analysis Tutorial

Enter input gene and choose the following option:

  • GENE EXPRESSION DATA Open
    • First, choose your gene expression data. Information about cohorts : microarrays, Affymetrix®, METABRIC, TCGA or SCAN-B (aka GSE81540 = GSE81538 + GSE96058)

    Then fill the textbox with actualised* gene symbol or Affymetrix® probeset ID.

    *: see actualised web databases (e.g.: Ensembl, GeneCards, HGNC, NCBI Gene...)

    @: the probesets followed by "@" are described as references for subtyping ER, PR and HER2 status by means of transcriptomics data. See Kenn et al..

  • DNA microarrays
    		• (n = 10 872)
  		• (n = 5 183)
  		• (n = 1 980)
  • RNA-seq
    		• (n = 4 421)
  		• (n = 743)
  		• (n = 3 678)

  • POPULATION Open
    • All combination of the clinical characteristics (nodal, oestrogen and progesterone receptor status) from the cohorts will be explored.

    All kind of event used for survival analyses will be taken into account:
    • "distant metastasis-free survival" (DMFS): first pejorative event represented by distant relapse.
    • "overall survival" (OS): first pejorative event represented by death.
    • "disease-free survival" (DFS): first pejorative event represented by any relapse or death.
    These datasets are retrieved from published annotated transcriptomic data.

    All criteria of population's section from targeted prognostic analysis module will be taken into account.
  • DISCRETISATION Open
    • Choose one of the radio button to select which splitting method you want to explore for prognostic study:
    • "mediane": 2 groups split at 50%,
    • "tertile": 3 groups split at 33%,
    • "quartile": 4 groups split at 25%,
    • "optimal": 2 groups split at the best cut-off (more details)
    • "custom percentile": 2 groups split at the user cut-off.

  • Splitting criterion:


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