Subtyping of Gliomaby Combining Gene Expression and CNVs Data Based on a Compressive Sensing Approach.
Subtyping of Gliomaby Combining Gene Expression and CNVs Data Based on a Compressive Sensing Approach.
复制标题
DOI：
10.4172/2169-0111.1000101
复制
发表时间：
2012-01-16
期刊：
影响因子：
--
通讯作者：
Wang YP
中科院分区：
文献类型：
--
作者：
Tang W;Cao H;Zhang JG;Duan J;Lin D;Wang YP
人们意识到，不同类型的基因组测量的组合分析往往会给出更可靠的分类结果。然而，如何有效地组合不同分辨率的数据是具有挑战性的。我们提出了一种新的基于压缩感知的方法，用于基因表达和拷贝数变异数据的联合分析，目的是对六种类型的胶质瘤进行亚型划分。实验结果表明，与单独使用任何一种数据类型相比，所提出的组合方法可以显著提高分类精度。所提出的方法可以适用于许多其他类型的基因组数据。
It is realized that a combined analysis of different types of genomic measurements tends to give more reliable classification results. However, how to efficiently combine data with different resolutions is challenging. We propose a novel compressed sensing based approach for the combined analysis of gene expression and copy number variants data for the purpose of subtyping six types of Gliomas. Experimental results show that the proposed combined approach can substantially improve the classification accuracy compared to that of using either of individual data type. The proposed approach can be applicable to many other types of genomic data.