Identifying underlying factors in breast cancer using independent component analysis

J. A. Berger, S. Hautaniemi, H. Edgren, O. Monni, S. Mitra, O. Yli-Harja, J. Astola
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引用次数: 12

Abstract

Independent component analysis is a well-known tool for extracting underlying mechanisms from an observed set of parallel data. Identifying such components in breast cancer cell lines, for both copy number and gene expression, is proposed here with the goal of identifying mechanisms that affect the evolution of breast cancer in humans. This paper illustrates how to utilize independent component analysis on cell line data for achieving this goal. After the components were estimated for the well-studied chromosome 17, and then over the entire genome for a set of 14 different breast cancer cell lines, ontological analysis was performed in order to determine common gene functions that are present in each of the independent components.
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使用独立成分分析确定乳腺癌的潜在因素
独立成分分析是一种众所周知的工具,用于从观察到的一组并行数据中提取潜在机制。在乳腺癌细胞系中识别这些成分,包括拷贝数和基因表达,目的是确定影响人类乳腺癌进化的机制。本文阐述了如何利用细胞系数据的独立成分分析来实现这一目标。在对已经得到充分研究的17号染色体的成分进行估计之后,然后对14种不同乳腺癌细胞系的整个基因组进行分析,进行本体论分析,以确定每个独立成分中存在的共同基因功能。
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