Krzyzanowski Paul M, Andrade-Navarro Miguel A
Molecular Medicine, Ottawa Health Research Institute, 501 Smyth Road, Ottawa, Ontario, K1H 8L6, Canada.
Genome Biol. 2007;8(9):R193. doi: 10.1186/gb-2007-8-9-r193.
We describe a method for detecting marker genes in large heterogeneous collections of gene expression data. Markers are identified and characterized by the existence of demarcations in their expression values across the whole dataset, which suggest the presence of groupings of samples. We apply this method to DNA microarray data generated from 83 mouse stem cell related samples and describe 426 selected markers associated with differentiation to establish principles of stem cell evolution.
我们描述了一种在大量异质基因表达数据集中检测标记基因的方法。通过整个数据集中表达值的分界来识别和表征标记，这些分界表明存在样本分组。我们将此方法应用于从83个小鼠干细胞相关样本生成的DNA微阵列数据，并描述了426个与分化相关的选定标记，以确立干细胞进化的原则。
