Associating functional groups to multiple clinical types using combined t-test scores and contingency-based measures: A study on breast cancer genes

Noha Yousri, Dalal M. Elkaffash

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Stemming from the need to score relations between functional groups of genes and multiple clinical types associated with a tumour, this study proposes to use contingency-based measures to quantify such relations. It aims at reflecting a relative measure of association within a specific set of functional groups, and a specific set of clinical statuses. The proposed methodology is based on extracting features (scores) from expression sets that relate genes to multiple cancer subtypes (clinical statuses), and use those features (scores) to associate cancer subtypes with functional groups. It proposes combining t-test scores at several levels of cancer statuses' differentiation to calculate such gene features. It also proposes using contingency based measures as Jaccard and F-measure to associate gene functional groups to multiple cancer subtypes/statuses. Variations from the original Jaccard measure are proposed to reflect scores of genes' relations to classes/groups rather than using binary relations. The core objective of the experimental study is to identify the functional categories of genes that mark the change in lymph node status under each of oestrogen receptor positive and negative statuses in breast cancer expression sets.

Original languageEnglish
Pages (from-to)261-283
Number of pages23
JournalInternational Journal of Computational Biology and Drug Design
Volume5
Issue number3-4
DOIs
Publication statusPublished - 1 Sep 2012
Externally publishedYes

Fingerprint

Neoplasm Genes
Functional groups
Genes
Breast Neoplasms
Neoplasms
Estrogen Receptors
Tumors
Lymph Nodes

Keywords

  • Breast cancer
  • Clinical status
  • Enrichment analysis
  • F-measure
  • Functional groups
  • Gene expression analysis
  • Gene ontology
  • Jaccard similarity
  • Lymph nodes
  • Oestrogen receptors
  • T-test

ASJC Scopus subject areas

  • Drug Discovery
  • Computer Science Applications

Cite this

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