关于白血病亚型基因芯片数据资料的后综分析

针对筛选特定癌症亚型的特异表达基因,提出了一种新颖的癌症基因芯片的后综分析方法——运用并改进秩打分算法(RS),对有序基因列表的统计均值取秩并打分.该算法结合常用的“一对多”(OVA)比对方法或“一对一”(OVO)比对方法,在跨平台检测某些白血病亚型特异基因时显得极为有效.6个公开的白血病数据的统计结果显示白血病亚型间的分子生物信号差异强于芯片系统间的差异.此外,一组儿童白血病亚型(BCR-ABL)的标志基因能够准确预测成人白血病中的该亚型.结果有助于从白血病或其他有着充分研究背景的癌症芯片表达数据中,发现、确认和治疗其亚型.

Meta-analysis gene lists about subtypes of leukemia based on gene expression data

To screen for molecular signatures that are commonly dysregulated in subtypes of a certain cancer,a novel meta-analysis is designed to perform rank score (RS) on lists of genes that are derived from different studies.RS is a promising way to detect signatures across platforms when integrating with one vs.all (OVA) or one vs.one (OVO) schemes of comparison.Among six published microarray expression datasets on acute leukemia,the biological signals hereafter provide stronger clustering support than systematic differences among microarray platforms.Moreover,the pediatric BCR_-ABL specific genes can be used to correctly discriminate independent adult BCR_-ABL cases.The obtained results redound to discover,validate and treat the subtypes from microarray gene expression profiles of cancer,which have been plentifully researched, such as leukemia.