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ENUMERATING SETS OF GENOMIC ALTERATIONS CHARACTERIZING A USER-DEFINED SUBGROUP

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Jennifer Wong
  • Function : Author
  • PersonId : 1093982
Thomas Pichetti
  • Function : Author
  • PersonId : 966578
François Radvanyi
  • Function : Author
  • PersonId : 992573

Abstract

Genetic alterations driving cancer are known to be spread over a large number of genes. Deciphering driver alterations from passenger alterations that may however be selected by single gene analysis is a major challenge. Alterations that characterize a given subtype of cancer are of particular interest. However, characterizing alteration sets rather then handling single alterations is a difficult task because of the combinatorial explosion of the number of sets. We consider a set of gene amplifications, deletions or mutations in tumor samples for which the subtypes of a given cancer are known. We consider that an alteration set characterizes a given subtype with respect to the others if they are frequent in that given subtype and rare for the others. We propose an efficient algorithm that outputs a ranked list of such alteration sets or pathways. The relevance of the output is illustrated using alteration data on bladder cancer.
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Dates and versions

hal-03174404 , version 1 (19-03-2021)

Identifiers

  • HAL Id : hal-03174404 , version 1

Cite

Jennifer Wong, Thomas Pichetti, François Radvanyi, Etienne E. Birmelé. ENUMERATING SETS OF GENOMIC ALTERATIONS CHARACTERIZING A USER-DEFINED SUBGROUP. 2021. ⟨hal-03174404⟩
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