Abstract: Systems and methods for determining cross-talk coefficients in curves, such as sigmoid-type or growth curves, and PCR curves and nucleic acid melting curves in particular, as well as for applying the cross-talk coefficients to produce cross-talk corrected data sets using a linear subtractive model. Cross-talk signal coefficients are determined using cross-talk data acquired across the entire signal acquisition range. Analyzing across all of the signal curve data provides for a more robust cross-talk correction across the entire data acquisition range. A linear subtractive model is used to correct data sets having cross-talk components.

Abstract: Systems and methods for identifying and removing spikes in data sets representing PCR growth curves or other sigmoid type curves or growth curves. A double sigmoid function with parameters determined using a Levenberg-Marquardt regression algorithm is used to find an approximation to the curve, and a statistical test such as a z-test is then used to identify spikes by identifying data points in the data set that do not fit well with the approximation. The identified spike(s) are removed from the data set and/or replaced with interpolated data points determined by using data points surrounding the identified spike(s). In one aspect, a spline interpolation process such as a cubic spline interpolation process is used to find an approximation to the data set with the identified spike points removed. Interpolated values to replace the spike points are then calculated using the cubic spline interpolation approximation curve.

Abstract: Systems and methods for determining characteristic transition values such as elbow values in sigmoid or growth-type curves, such as the cycle threshold (Ct) value in PCR amplification curves. A double sigmoid function with parameters determined by a Levenberg-Marquardt (LM) regression process is used to find an approximation to a curve that fits a PCR dataset. Once the parameters have been determined, the curve can be normalized using one or more of the determined parameters. Normalization is advantageous for determining the Ct value if one chooses the arbitrary fluorescence level (AFL) approach to calculating Ct values for amplification curves. After normalization, the normalized curve is processed by applying a root-finding algorithm to determine the root of the function representing the normalized curve, which root corresponds to the Ct value. The Ct value is then returned and may be displayed or otherwise used for further processing.

Abstract: Analytical multi-spectral optical detection systems and methods. A light source provides one or multiple lines (e.g., discrete wavelengths) of high spectral purity excitation light that is optically coupled to a sample via delivery fiber optic cables. Emission light is collected and provided to an emission detector, such as a diffraction gradient spectrophotometer emission detector, using collection fiber optic cables bundled with the delivery fiber optic cables in a probe interface positioned proximal a sample holder. The probe interface may be scanned over one or more samples, or one or more samples may be scanned proximal a fixed interface probe. Multiple excitation wavelengths allows for simultaneous excitation and detection of multiple fluorescent dyes in the visible spectrum. This increases sample throughput and reduces signal variations associated with signal acquisition at different times.

Abstract: 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.

Abstract: Systems and methods for determining the elbow or Ct value in a real-time, or kinetic, PCR amplification curve data set. 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 k?3. 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.

Abstract: A method is provided for continually or continuously measuring the concentration of target chemical analytes present in a biological system, and processing analyte-specific signals to obtain a measurement value that is closely correlated with the concentration of the target chemical analyte in the biological system. One important application of the invention involves a method for signal processing in a system for monitoring blood glucose values.

Abstract: Systems and methods for determining the elbow or Ct value in a real-time, or kinetic, PCR amplification curve data set. A PCR data set may be visualized in a two-dimensional plot of fluorescence intensity vs. cycle number. The data set may be adjusted to have a zero slope. In one aspect, a data set is fit to a double sigmoid curve function with the function parameters determined using a Levenberg-Marquardt regression process. The determined parameters are used to subtract off the linear growth portion from the data set to provide a modified data set. For multiple data sets, all the data curves can be aligned in this manner to have a common baseline slope, e.g., a slope of zero. A rotation transform is applied to a modified data set to rotate the data about a defined coordinate such as the origin so that the data point representing the Ct value becomes a minimum or a maximum along the intensity axis.

Abstract: Systems and methods for determining the elbow or Ct value in a real-time, or kinetic, PCR amplification curve data set. The PCR data set may be visualized in a two-dimensional plot of fluorescence intensity vs. cycle number. A rotation transform is applied to the data set to rotate the data about a defined coordinate such as the origin so that the data point representing the Ct value becomes a minimum or a maximum along the intensity axis. The data point representing the elbow or Ct value of the PCR curve is identified, and this data point is then rotated back and the cycle number of the data point is returned or displayed.

Abstract: A microfluidics device and method for sample loading, concentrating, mixing, and/or reacting is disclosed. The device has a microchannel network that includes a channel segment communicating with first and second reservoirs. A projection formed on a wall portion of the channel segment terminates therein at a point or edge. When a voltage potential is applied across the two reservoirs, the projection functions to create an electric field gradient within the channel segment that causes charged components in the channel segment to concentrate in the region of the projection. The device is useful, for example, in loading a sample of dilute charged components for electrophoretic separation in the device.