| 摘要 |
Systems and methods for determining the cycle threshold (Ct) value in a kinetic PCR amplification curve. The PCR data set may be visualized in a two-dimensional plot of fluorescence intensity (y-axis) vs. cycle number (x-axis). The data set is transformed to produce a partition table of data points with one column including the fluorescence at cycle (n) and a second column including the fluorescence at cycle (n+i), where i is typically 1 or greater. A cluster analysis process is applied to the partition table data set to determine a plurality of clusters in the partition table data set. In one aspect, the clustering process used includes a k-means clustering algorithm, where the number of identified clusters, k, is greater than or equal to three. In another aspect, a Partitioning Around Medoids (PAM) algorithm is used to identify three or more clusters. Using the identified clusters, a linear slope of each of the clusters is determined based on y(n+1) vs. n, and for each cluster, a ratio of the slope of that cluster with the slope of an adjacent cluster is determined. The ratios are then compared. An end point of a cluster having the largest or smallest ratio represents a specific point of interest in the data curve. The data point representing the elbow or Ct value of the PCR curve is identified as an end point of one of the identified clusters, and the cycle number corresponding to this data point is returned or displayed.
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