Introduction to Flow Cytometry A Learning Guide流式细胞术介绍：学习指南

1027429345 医器二班 赵桂琴

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Introduction to Flow Cytometry: A Learning Guide流式细胞术介绍：学习指南

5.3 Data Analysis for Subsetting Applications细胞亚群的数据分析

Data analysis consists of displaying the data from a list-mode file in a plot, then measuring the distribution of the events within the plots. As mentioned earlier, several types of plots can be used to present the data. Data can also be subdivided by gating upon specific populations.

数据分析包括从点图中的list-mode文件中显示数据,然后统计点图中的细胞分布情况。如前所述，分别有几种形式的点图用于显示数据，而且可通过设门的方法区分指定的细胞亚群。 For example, in the dot plot shown in Figure 5-3, a gate is drawn around the population of interest, which in this case is the lymphocytes. A gate or a region is a boundary drawn around a subpopulation to isolate events for analysis or sorting. 如图5-3所示，在淋巴细胞亚群周围设门，以单独分析或分选该亚群细胞。门或一个区域是亚群孤立事件分析或排序的周围绘制边界。

Figure 5-3 Dot plot with a gate encompassing the lymphocyte population 图5-3 选定淋巴细胞亚群设门

Data for events within this gate can then be displayed in subsequent plots. In the examples that follow, you will see different ways to analyze fluorescence data from events in this gate to determine the percentages of various subpopulations (subsets) present.

门内细胞的数据结果可在随后的图中显示。在下面的实例中，我们将详尽阐述细胞亚群百分含量的不同分析方法。。

You can make a single-parameter histogram plot with histogram markers, a twoparameter dot plot with a quadrant marker, a two-parameter dot plot with regions, and three-dimensional plots. You can also create statistics and export the results that are associated with these plots to a spreadsheet. 你可以做一个单一参数直方图，双参数点图的一个象限标记图，与一个区域的一个双参数点图，和三维图。可以建立数据统计表以输出结果。

A histogram allows you to view a single parameter against the number of events. A subclass control is used to determine where the markers will be placed. Histogram markers are used to specify a range of events for a single parameter (Figure 5-4). On the first histogram, marker M1 is placed around the negative peak of the subclass control. Marker M2 is placed to the right of M1 to designate positive events. The second histogram shows events from a CD3 FITC sample.

从直方图可以让你查看一个单一的参数对事件的数量。一子类控制用于确定将被放置标记。在第一个柱状图,标记M1是放置的负峰值控制。阴性对照用于决定直方图中单参数的左右边界（见图5-4）。左图中M1为阴性对照峰。右图中M2为CD3 FITC阳性峰。

Figure 5-4 Histograms of subclass control (NORM001) and CD3 FITC (NORM002) with histogram markers M1 and M2

图5-4 阴性对照峰M1（NORM001）和CD3 FITC阳性峰M2（NORM002）

Figure 5-5 shows 619 events in M1 and 2272 in M2. To find out statistical percentages of the negatives and the positives, compare the event count with the gated events. There are 6000 events in the data file, but 2891 events found inside the lymphocyte gate. We want the percentage of lymphocytes that are CD3 positive, so we would look at the %Gated for M2: 2272/2891 = 78.59%.

图5-5的统计结果表明，整个事件共记录了6000个细胞，门内淋巴细胞2891个。其中M1（阴性）细胞619个，M2（CD3阳性）细胞2272个细胞。淋巴细胞亚群CD3阳性百分 含量的统计结果为：M2：2272/2891=78.59%。

Figure 5-5 Histogram statistics 图5 - 5直方图统计结果

A dot plot provides a two-parameter display of data. Each dot represents one or more events. The first dot plot in Figure 5-6 is the isotope or subclass control. A subclass control is used to determine where the quadrant markers will be placed. A quadrant marker divides two-parameter plots into four sections to distinguish populations that are considered negative, single positive, or double positive. The lower-left quadrant displays events that are negative for both parameters. The upper-left quadrant contains events that are positive for the y-axis parameter (CD19 PE) but negative for the x-axis (CD3 FITC) parameter. The lower-right quadrant contains events that are positive for the x-axis parameter (CD3 FITC) but negative for the y-axis (CD19 PE) parameter. The upper-right quadrant contains events that are positive for both parameters (CD19+/CD3+), or double positive.

二维点图以双参数显示结果，每个点表示一个或多个细胞。图5-6为阴性对照图，用于设定阴性对照边界，全图划分为四个象限，以区分阴性细胞、单阳性细胞以及双阳性细胞。左下象限（LL）为双阴性细胞，左上象限（UL）为Y轴阳性细胞（CD19 PE），左下象限（LR）为X轴阳性细胞（CD3 FITC），右上象限（UR）为双阳性细胞（CD19+/CD3+）。

Figure 5-6 Dot plots of subclass control (NORM001) and CD3 FITC/CD19 PE(NORM002) with quadrant markers

图5-6 阴性对照组(NORM001)和CD3 FITC/CD19 PE双染样本(NORM002)

To find out the percentages of CD19+/CD3- lymphocytes, look at the %Gated of the upper left (UL) quadrant divided by gated events (Figure 5-7): 296/2839 = 10.43%.

如图5-7所示，淋巴细胞亚群双阳性细胞（CD19+/CD3+）的百分含量为：296/2839=10.43%。

Figure 5-7 Quadrant statistics 图5-7散点图统计结果

An alternative way to get statistics is to create regions around the populations instead of using a quadrant marker. You can create differently shaped regions (Figure 5-8); then use region statistics to find out the percentages of specific populations. In Figure 5-9, the %Gated of R4 is the CD3–/CD4+ lymphocytes: 40/2866 = 1.40%.

图5-7 散点图统计结果 另一个分析方法是划定区域，也就是设门。我们可以用不同形状的绘图工具定义所选区域（如图5-8所示）；然后统计该区域内指定细胞亚群的百分含量。在图5-9中，R4门内为CD4阳性，CD3阴性的淋巴细胞亚群，其结果为：40/2866=1.40%。

Figure 5-8 Dot plot of CD3 FITC/CD4 PE with four regions 图5-8 CD3 FITC/CD4 PE 双染样本分析图

Figure 5-9 Region statistics 图5-9 CD3 FITC/CD4 PE 双染样本数据统计结果

There is a disadvantage to using both of these analysis methods if you have several files to analyze from different donor samples. If you had drawn the regions around populations or created

quadrant markers from one data file and then read in another file, it is possible that the populations will fall outside the regions or markers due to sample variability. In this case, you would have to readjust the regions or markers for every file.

这种方法在分析不同的供体细胞时存在一个缺陷，因为如果事先定义好细胞亚群的区域或边界，在随后的文件中，下一个样本的细胞亚群位置会发生变化，这就需要操作者重新调整区域或边界位置。

There is a new analysis method available to avoid this situation. This innovative technology is called cluster analysis. BD Multi SETTM and Attractors TM software use cluster analysis to analyze data. In these software programs, regions shift their positions to encompass clusters from one data file to the next (Figure 5-10).

有一个新的分析方法，以避免这种情况。我们采用一种称为集群分析（cluster analysis）的新方法。BD公司的MultiSETTM 和AttractorsTM软件就属于集群分析软件。该软件的特点是会随着整个细胞亚群的移动而移动，自动变换区域或边界到相应的细胞亚群位置（见图

。 5-10）

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