论文标题
肿瘤基因组DNA的拉曼光谱的统计分类
Statistical classification for Raman spectra of tumoral genomic DNA
论文作者
论文摘要
我们利用表面增强的拉曼散射(SER)来研究沉积在银色涂层硅纳米线上的基因组DNA的水滴,我们表明可以有效区分肿瘤和健康细胞光谱。为了评估所提出技术的鲁棒性,我们开发了两种不同的统计方法,一种基于光谱数据的主要成分分析,另一个基于$ \ ell^2 $距离之间的计算。两种方法都非常有效,我们通过所谓的Cohen的$κ$统计来测试它们的准确性。我们表明,SERS光谱法和统计分析方法的协同组合导致有效且快速的癌症诊断应用,从而使健康和肿瘤基因组DNA替代更复杂且昂贵的DNA测序替代方案。
We exploit Surface-Enhanced Raman Scattering (SERS) to investigate aqueous droplets of genomic DNA deposited onto silver-coated silicon nanowires and we show that it is possible to efficiently discriminate between spectra of tumoral and healthy cells. To assess the robustness of the proposed technique, we develop two different statistical approaches, one based on the Principal Component Analysis of spectral data and one based on the computation of the $\ell^2$ distance between spectra. Both methods prove to be highly efficient and we test their accuracy via the so-called Cohen's $κ$ statistics. We show that the synergistic combination of the SERS spectroscopy and the statistical analysis methods leads to efficient and fast cancer diagnostic applications allowing a rapid and unexpansive discrimination between healthy and tumoral genomic DNA alternative to the more complex and expensive DNA sequencing.