Abstract:
The present teachings relate to embodiments of systems and methods for the analysis of melt curve data for a plurality of samples. According to various embodiments, a melting temperature (Tm) may be determined across a range of different types of protein melt curve data, having variability over a plurality of analytical attributes in order to accommodate the complexity of protein melt curve data. The combination of a plurality of samples, coupled with the complexity of the data gives rise for a need to process the data in a manner that readily facilitates end-user to analysis of the data. Various embodiments of an interactive graphical user interface (GUI) according to the present teachings provide for rapid and sequential changes that may be made by an end user to displayed protein melt curve data to allow such analysis.
Abstract:
Systems and methods for assigning attributes to a plurality of samples are provided. An exemplary system includes an instrument configured to perform an experiment on a plurality of samples in a multi- sample support device and to produce a plurality of measured values. The system further includes a computer system in communication with the instrument. The computer system is configured to receive the plurality of measured values from the instrument, store the plurality of measured values in a memory configured as a grid of cells representing the grid of the multi- sample support device, display the grid of cells in a graphical user interface, receive a selected cell from the graphical user interface, receive two or more attribute values for the selected cell from the graphical user interface, and store the two or more assigned attribute values along with a measured value of the selected cell in the memory configured as a grid of cells.
Abstract:
Methods for the determination of a copy number of a target genomic sequence; either a target gene or genomic sequence of interest, in a biological sample are described. Various methods utilize a model drawn from a probability density function (PDF) for the assignment of a copy number of a target genomic sequence in a biological sample. Additionally, the methods provide for the determination of a confidence value for a copy number assigned to a sample based on attributes of the sample data. Accordingly, the various methods for the determination of a copy number provide the end user with significant information for the evaluation of a copy number of a target genomic sequence; either a gene or genomic sequence of interest.
Abstract:
Systems and methods according to embodiments of the present teachings incorporate a set of possible signal transforms that can be used to examine the baseline region of an amplification profile for noise. In embodiments, a difference time series analysis can be performed to determine deviations of detected fluorescent or other signal intensity in the early cycles of a PCR or other reaction over a median difference time series magnitude. In embodiments, difference time series analysis or other detection techniques can be performed over different hop sizes producing a multi-resolution analysis. In embodiments, the amplification profile can be transmitted to a set of noise detectors whose individual results or decisions are polled or weighted to determine the presence of noise in the baseline or other region. In embodiments, a second derivative analysis on the baseline region can be performed.
Abstract:
A proximity binding assay (PBA) is performed on at least one test sample, at least one reference sample, a background sample, and one or more calibration samples using a thermal cycler instrument. Ct values are determined for at least one set of test sample data and at least one set of reference sample data. Background corrected Ct values are calculated using a corresponding value in a background sample data set. A linear range is determined for the background corrected Ct values as a function of sample quantity. A linear regression line is calculated for each linear range. One or more parameter values of an exponential model (EM) fold change formula are estimated from the one or more sets of calibration sample data. A target protein quantity and associated confidence interval are calculated using the linear regression lines and the EM fold change formula.
Abstract:
Methods for the determination of a copy number of a target genomic sequence; either a target gene or genomic sequence of interest, in a biological sample are described. Various methods utilize a model drawn from a probability density function (PDF) for the assignment of a copy number of a target genomic sequence in a biological sample. Additionally, the methods provide for the determination of a confidence value for a copy number assigned to a sample based on attributes of the sample data. Accordingly, the various methods for the determination of a copy number provide the end user with significant information for the evaluation of a copy number of a target genomic sequence; either a gene or genomic sequence of interest.
Abstract:
Systems and methods according to embodiments of the present teachings incorporate a set of possible signal transforms that can be used to examine the baseline region of an amplification profile for noise. In embodiments, a difference time series analysis can be performed to determine deviations of detected fluorescent or other signal intensity in the early cycles of a PCR or other reaction over a median difference time series magnitude. In embodiments, difference time series analysis or other detection techniques can be performed over different hop sizes producing a multi-resolution analysis. In embodiments, the amplification profile can be transmitted to a set of noise detectors whose individual results or decisions are polled or weighted to determine the presence of noise in the baseline or other region. In embodiments, a second derivative analysis on the baseline region can be performed.
Abstract:
Disclosed are genomic sequences for nine strains of Cronobacter spp. (C. sakazakii - 696, 701, 680; C. malonaticus - 507, 681; C. turicensis - 564; C. muytjensii - 530; C. dublinensis - 582; C. genomospl - 581) and compositions, methods, and kits for detecting, identifying and distinguishing Cronobacter spp. strains from each other and from non-Cronobacter spp. strains. Some embodiments describe isolated nucleic acid compositions unique to certain Cronobacter strains as well as compositions that are specific to all Cronobacter spp. Primer and probe compositions and methods of use of primers and probes are also provided. Kits for identification of Cronobacter spp. are also described. Some embodiments relate to computer software methods for setting a control based threshold for analysis of PCR
Abstract translation:公开了九个克罗杆菌属菌株的基因组序列。 (C. sakazakii-696,701,680; C. malonaticus-507,681; C. turicensis-564; C. muytjensii-530; C.dublinensis-582; C.基因组蛋白-58)和组合物,方法和试剂盒 用于检测,识别和鉴别克罗杆菌属。 菌株彼此和非克罗杆菌属。 株。 一些实施方案描述了某些克罗杆菌菌株特有的分离的核酸组合物以及对所有克罗杆菌属特异性的组合物。 还提供引物和探针组合物以及引物和探针的使用方法。 克隆杆菌属鉴定试剂盒 也被描述。 一些实施例涉及用于设置用于PCR分析的基于控制的阈值的计算机软件方法
Abstract:
Disclosed are genomic sequences for nine strains of C ronobacter spp . (C. sakazakii - 696, 701, 680; C. malonaticus - 507, 681; C. turicensis - 564; C. muytjensii - 530; C. dublinensis - 582; C. genomospl - 581) and compositions, methods, and kits for detecting, identifying and distinguishing C ronobacter spp . strains from each other and from non-C ronobacter spp . strains. Some embodiments describe isolated nucleic acid compositions unique to certain C ronobacter strains as well as compositions that are specific to all C ronobacter spp . Primer and probe compositions and methods of use of primers and probes are also provided. Kits for identification of C ronobacter spp . are also described. Some embodiments relate to computer software methods for setting a control based threshold for analysis of PCR
Abstract translation:公开了九个克罗杆菌属菌株的基因组序列。 (C. sakazakii-696,701,680; C. malonaticus-507,681; C. turicensis-564; C. muytjensii-530; C.dublinensis-582; C.基因组蛋白-58)和组合物,方法和试剂盒 用于检测,识别和鉴别克罗杆菌属。 菌株彼此和非克罗杆菌属。 株。 一些实施方案描述了某些克罗杆菌菌株特有的分离的核酸组合物以及对所有克罗杆菌属特异性的组合物。 还提供引物和探针组合物以及引物和探针的使用方法。 克隆杆菌属鉴定试剂盒 也被描述。 一些实施例涉及用于设置用于PCR分析的基于控制的阈值的计算机软件方法
Abstract:
A proximity binding assay (PBA) is performed on at least one test sample, at least one reference sample, a background sample, and one or more calibration samples using a thermal cycler instrument. Ct values are determined for at least one set of test sample data and at least one set of reference sample data. Background corrected Ct values are calculated using a corresponding value in a background sample data set. A linear range is determined for the background corrected Ct values as a function of sample quantity. A linear regression line is calculated for each linear range. One or more parameter values of an exponential model (EM) fold change formula are estimated from the one or more sets of calibration sample data. A target protein quantity and associated confidence interval are calculated using the linear regression lines and the EM fold change formula.