Measuring cell identity in noisy biological systems

Measuring cell identity in noisy biological systems
复制标题

DOI:
10.1093/nar/gkr591
复制
发表时间:
2011-11-01
影响因子:
14.9
通讯作者:
Kussell, Edo
Kussell, Edo
中科院分区:
生物学2区
文献类型:
--
作者:
Birnbaum, Kenneth D.;Kussell, Edo

文献摘要

被引文献

相似文献

全球基因表达测量越来越多地作为细胞类型、组织内的空间位置和其他生物学意义的坐标的函数而获得。这样的数据应该能够对基因表达的细胞类型特异性进行定量分析,但这种分析往往会因噪声的存在而受到干扰。我们引入了一个特异度指标Spec,它量化了关于任何给定细胞类型的基因完整表达谱中的信息,以及一个不确定性指标DSPEC,它衡量了噪声对特异度的影响。使用来自小鼠大脑、植物根和人类白细胞的全球基因表达数据,我们表明Spec识别出表达水平可变的基因,但这些基因对特定细胞类型具有高度特异性。当使用来自不同个体的样本时,DSPEC测量每种细胞类型中基因的转录可塑性。我们的方法广泛适用于干细胞生物学、发育生物学、癌症生物学和生物标记物鉴定中定位的基因表达测量。作为这类应用的一个例子,我们展示了Spec识别一类新的生物标记物,这些生物标记物表现出可变的表达而不影响特异性。该方法为量化噪声存在下的特异性提供了一个统一的理论框架,它广泛适用于不同的生物系统。
Global gene expression measurements are increasingly obtained as a function of cell type, spatial position within a tissue and other biologically meaningful coordinates. Such data should enable quantitative analysis of the cell-type specificity of gene expression, but such analyses can often be confounded by the presence of noise. We introduce a specificity measure Spec that quantifies the information in a gene's complete expression profile regarding any given cell type, and an uncertainty measure dSpec, which measures the effect of noise on specificity. Using global gene expression data from the mouse brain, plant root and human white blood cells, we show that Spec identifies genes with variable expression levels that are nonetheless highly specific of particular cell types. When samples from different individuals are used, dSpec measures genes' transcriptional plasticity in each cell type. Our approach is broadly applicable to mapped gene expression measurements in stem cell biology, developmental biology, cancer biology and biomarker identification. As an example of such applications, we show that Spec identifies a new class of biomarkers, which exhibit variable expression without compromising specificity. The approach provides a unifying theoretical framework for quantifying specificity in the presence of noise, which is widely applicable across diverse biological systems.