Gao Cuilan, Cheng Cheng
Department of Biostatistics, St Jude Children’s Research Hospital, Memphis, TN 38105, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:6837-40. doi: 10.1109/IEMBS.2011.6091686.
An immediate challenge in integrated genomic analysis involving several types of genomic factors all measured genome-wide is the ultra-high dimensionality. Screening all possible relationships among the genomic factors is an NP-hard problem; therefore in practice proper dimension reduction is necessary. In this paper we develop the Phenotype-Driven Dimension Reduction (PhDDR) approach to the analysis of gene co-expressions, and discuss its extensions to integration of other genetic factors. This approach is then illustrated by an application to gene co-expression analysis of treatment response of childhood leukemia.
在涉及全基因组测量的多种类型基因组因素的综合基因组分析中，一个直接的挑战是超高维度。筛查基因组因素之间所有可能的关系是一个NP难问题；因此在实践中进行适当的降维是必要的。在本文中，我们开发了用于基因共表达分析的表型驱动降维（PhDDR）方法，并讨论了其在整合其他遗传因素方面的扩展。然后通过将其应用于儿童白血病治疗反应的基因共表达分析来说明该方法。
