Associating functional groups to multiple clinical types using combined t-test scores and contingency-based measures: a study on breast cancer genes
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 functi...
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Published in | International journal of computational biology and drug design Vol. 5; no. 3-4; p. 261 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
England
2012
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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. |
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AbstractList | 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. |
Author | Yousri, Noha A Elkaffash, Dalal M |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23013653$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Breast Neoplasms - genetics Breast Neoplasms - pathology Female Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Lymph Nodes - pathology Lymphatic Metastasis - genetics Receptors, Estrogen - genetics |
Title | Associating functional groups to multiple clinical types using combined t-test scores and contingency-based measures: a study on breast cancer genes |
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