Shlemov Alex, Golyandina Nina, Holloway David, Spirov Alexander
Faculty of Mathematics and Mechanics, St. Petersburg State University, Universitetsky Pr. 28, Peterhof, St. Petersburg 198504, Russia.
Mathematics Department, British Columbia Institute of Technology, 3700 Willingdon Avenue, Burnaby, BC, Canada V5G 3H2.
Biomed Res Int. 2015;2015:689745. doi: 10.1155/2015/689745. Epub 2015 Mar 19.
In recent years, with the development of automated microscopy technologies, the volume and complexity of image data on gene expression have increased tremendously. The only way to analyze quantitatively and comprehensively such biological data is by developing and applying new sophisticated mathematical approaches. Here, we present extensions of 2D singular spectrum analysis (2D-SSA) for application to 2D and 3D datasets of embryo images. These extensions, circular and shaped 2D-SSA, are applied to gene expression in the nuclear layer just under the surface of the Drosophila (fruit fly) embryo. We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo. We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes. Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.
近年来，随着自动化显微镜技术的发展，基因表达图像数据的数量和复杂性急剧增加。定量和全面分析此类生物数据的唯一方法是开发和应用新的复杂数学方法。在此，我们展示了二维奇异谱分析（2D-SSA）的扩展，用于应用于胚胎图像的二维和三维数据集。这些扩展，即圆形和形状二维奇异谱分析，应用于果蝇胚胎表面下核层中的基因表达。我们考虑了椭圆形果蝇胚胎常用的柱面投影。我们展示了二维奇异谱分析的圆形和形状版本如何有助于将表达数据分解为可识别的成分（如趋势和噪声），以及分离来自不同基因的信号。还讨论了多通道成像中欠校正和过校正的检测与改进，以及三维基因表达模式中三维特征的提取与分析。
