使用联合t检验分数和基于偶然性的措施将功能群与多种临床类型联系起来:一项关于乳腺癌基因的研究。

Q4 Pharmacology, Toxicology and Pharmaceutics International Journal of Computational Biology and Drug Design Pub Date : 2012-01-01 Epub Date: 2012-09-24 DOI:10.1504/IJCBDD.2012.049208
Noha A Yousri, Dalal M Elkaffash
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引用次数: 1

摘要

由于需要对与肿瘤相关的基因功能群和多种临床类型之间的关系进行评分,本研究建议使用基于偶然性的措施来量化这种关系。它旨在反映一组特定功能组和一组特定临床状态之间关联的相对度量。所提出的方法是基于从基因与多种癌症亚型(临床状态)相关的表达集中提取特征(分数),并使用这些特征(分数)将癌症亚型与功能组联系起来。它建议结合不同癌症状态分化水平的t检验分数来计算这些基因特征。它还建议使用基于偶然性的措施,如Jaccard和F-measure,将基因功能组与多种癌症亚型/状态联系起来。从原来的Jaccard测量的变化被提出,以反映分数的基因与类/组的关系,而不是使用二元关系。本实验研究的核心目的是确定乳腺癌表达集中雌激素受体阳性和阴性状态下淋巴结状态变化标志基因的功能类别。
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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 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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来源期刊
International Journal of Computational Biology and Drug Design
International Journal of Computational Biology and Drug Design Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
CiteScore
1.00
自引率
0.00%
发文量
8
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