Integrated Center for Oncology

Breast Cancer Gene-Expression Miner v5.0
(bc-GenExMiner v5.0)

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Gene correlation targeted analysis Tutorial

Enter input genes and choose one of the following options:

  • GENES EXPRESSION DATA Open
    • First, choose your gene expression data. Information about cohorts : microarrays or RNA-seq

    Then fill the textbox with actualised* gene symbol.
    For more than two genes, identifiers must be separated by ";" (e.g.: UBE2C;LMNB1).

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

  • DNA microarrays
    		• (n = 10 872)
    Clear allClear
  • RNA-seq
    		• (n = 4 421)

    		Open
    The uploaded file must comply with all following criteria:
    • file with tabulation, space, comma or newline separated values,
    • file type from among the following extensions: .csv, .tsv or .txt,
    • file containing only gene symbols (not full names or descriptions),
    • file with a maximum items of 20 gene symbols,
    • file with a maximum size of 10 Kbytes.

  • POPULATION Open
    • Choose one of the radio button to select which population you want to explore.

    This analysis is only available with all DNA microarrays or all RNAseq data.
    This option allows to explore triple-negative breast cancer (TNBC) (IHC) subtypes (LAR, MLIA, BLIA and BLIS):
    • LAR: luminal androgen receptor,
    • MLIA: mesenchymal-like immune-activated,
    • BLIA: basal-like immune-activated,
    • BLIS: basal-like immune-suppressed.

  • OUTPUT CORRELATION FIGURE Open
    • Choose one of the radio button to select which output figure you want to get as a result plot.
    Have a sneak peak of each figure by clicking on following options available:

  • Type of plot:


    • Legend Open
     IHC:immunohistochemistry
     PAM50:Parker's instrinsic molecular subtypes
     RIMSPC:robust intrinsic molecular subtype predictors classification based on patients classified in the same subtype with the six molecular subtype predictors (3 SSPs + 3 SCMs)
     RSCMC:robust SCM classification based on patients classified in the same subtype with the three SCMs
     RSSPC:robust SSP classification based on patients classified in the same subtype with the three SSPs
     SCM:Subtype clustering model (SCMOD1, SCMOD2 or SCMGENE)
     SSP:single sample predictor (Sorlie's, Hu's or PAM50)
     TNBC:triple-negative breast cancer; tumours negative for oestrogen and progesterone receptors and epidermal growth factor receptor 2 (HER2), by means of IHC


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