PRINCIPAL COMPONENT/BIPLOT ANALYSES FOR CELL SORTING

将转换多参数流式细胞术（FCM）数据 在实验过程中产生（使用主成分 或基于其它投影追踪方法的投影）两个 多维数据的多维投影， 细胞亚群的可视化和分选。 双标图a 强大的新技术， 每个亚群的多个FCM参数之间 将被用来研究生物学和生物学之间的基本关系 这些参数可能会对基本生物学提供新的见解， 机制等 最有用的投影系数 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 electronics. 然后将原始参数转换为真实的- 时间到适当的主成分（或其他预测） 坐标 这将允许实时散点图和细胞 细胞亚群的分选，如细胞簇所示 投影空间中的子群体以及基于 始终保持相关的原始参数。 的能力 在物理上挑选出这些细胞亚群 主成分/双标图分析可以提供关键链接 通过复杂流式细胞术定义的亚群之间 测量及其生物学重要性， 功能和其他分析，我们将在这些 孤立的细胞 这些新方法将专门应用于复杂的 来自孕妇血液的荧光数据。 此外，它还将与特殊的预处理产品结合在一起， 现有的高速稀有事件电路， 稀有人类胎儿细胞的多参数检测和分选 来自母亲的血液。 处理异常数据的新方法 点应允许改进稀有细胞的检测 亚群通常被“假阳性”掩盖。 这些新 方法具有普遍实用性，可为其他研究人员提供 使用流式细胞术和强大的新可视化方法 复杂的，难以解释的数据和分离的方法 新的细胞亚群至关重要。

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.