PRINCIPAL COMPONENT/BIPLOT ANALYSES FOR CELL SORTING

多参数流式细胞仪(FCM)数据将被转换 在实验期间产生(使用两个主成分之一 或基于其他投影寻踪方法的投影)两个 的多维数据的多维投影 细胞亚群的可视化和分类。双点图，a 一种强大的关联可视化新技术 在每个子群体的多个FCM参数之间 将被用来观察生物之间的基本关系 这些参数可能会对基本生物学有新的见解 机械装置。最有用的投影的系数 数据(基于原始数据的线性或非线性组合 参数)将被下载到实时信号处理中 电子产品。然后，原始参数将被转换为实数- 到达适当主成分(或其他投影)的时间 坐标。这将允许实时散点图和单元 通过细胞团看到的细胞亚群的分类 投影空间中的子群体以及基于 始终保持关联的原始参数。一种能力 对这些细胞亚群进行物理分类 主成分/双曲线分析可以提供关键的联系 复杂的流式细胞术所定义的亚群间 测量及其生物学重要性，由定义 我们将对这些进行功能和其他分析 分离的细胞。 这些新方法将专门应用于复杂的 孕妇血液中的多色荧光数据。 此外，它还将与特殊预制件的输出相结合 现有的高速罕见事件电路允许改进 稀有人胎儿细胞的多参数检测与分选 来自母体的血液。处理异地数据的新方法 点数应允许改进稀有细胞的检测 亚群通常被“假阳性”所掩盖。这些新的 这些方法具有普遍的实用性，可以为其他研究人员提供 使用流式细胞术和强大的可视化新方法 复杂的、难以解释的数据和分离的手段 产生了至关重要的新细胞亚群。

Multiparameter flow cytometry (FCM) data will be transformed during experiments to produce (using either principal components or projections based on other projection pursuit methods) two dimensional projections of the multidimensional data for visualization and sorting of cell subpopulations. Biplots, a powerful new technique for visualization of the correlation between multiple FCM parameters of each of the subpopulations will be used to see fundamental relationships between biological parameters which may give new insights as to basic biological mechanisms. The coefficients of the most useful projections of the data (based on linear or non-linear combinations of raw parameters) will be downloaded into real-time signal processing electronics. The raw parameters will then be transformed in real- time to the appropriate principal component (or other projection) coordinates. This will permit real-time scattergrams and cell sorting of cell subpopulations as seen by clusters of cell subpopulations in the projection space as well as on the basis of raw parameters which remain correlated at all times. The ability to physically sort out these cell subpopulations on the basis of principal component/biplot analyses can provide the critical link between subpopulations as defined by complex flow cytometric measurements and their biological importance as defined by functional and other assays that we will be performing on these isolated cells. These new methods will be specifically applied to complex multicolor fluorescence data from the blood of pregnant mothers. Additionally it will be wedded to the output of special pre- existing high-speed rare-events circuitry to allow improved multiparameter detection and sorting of rare human fetal cells from maternal blood. New methods for dealing with outlying data points should allow for improved detection of rare cell subpopulations normally obscured by "false positives". These new methods are of general utility and could provide other researchers using flow cytometry with powerful new methods for visualization of complex, difficult to interpret, data and a means of separating out new cell subpopulations of fundamental importance.