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 method for generating a data visualization is provided. The method includes receiving a plurality of data points related to fluorescent emissions values from a plurality of reaction sites. The fluorescent emission values include information for a first type of dye and a second type of dye. The method further includes displaying a first portion of the plurality of data points related to the first type of dye in a representation of location of the plurality of reaction sites, and displaying a second portion of the plurality of data points related to the second type of dye in the representation. The method further includes displaying the first portion of the plurality of data points in a scatter plot display. The scatter plot shows fluorescent values related to the first dye on the y-axis and fluorescent values related to the second dye on the x-axis. The method includes displaying the second portion of the plurality of data points in the scatter plot display.
Abstract:
A method for generating a data visualization is provided. The method includes displaying a representation of a portion of detected data from a substrate to a user. The method further includes generating a data quality value for the portion of detected data and displaying, along with the representation of the portion of detected data, an indication of data quality value for the portion of detected data. The method further includes selecting, by the user, a quality value threshold, and displaying an adjusted indication of data quality value for the portion of detected data meeting the quality value threshold.
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:
A computer-implemented method for determining minor variants. The method includes receiving electropherogram sequence data from a test sample, identifying any non-primary peaks in the electropherogram, and characterizing identified non-primary peaks using at least one signal feature. The method may further include analyzing the at least one signal feature across identified non-primary peaks to identify variant candidates, evaluating at least one peak characteristic of each of the identified variant candidates, and classifying variant candidates as bona fide variants based on the evaluation of peak characteristics.
Abstract:
Systems and methods for detecting microsatellite instability in a biological sample are described. Signal data is received from a capillary electrophoresis genetic analysis instrument, wherein the signal data is measured from fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample via polymerase chain reaction (PCR). The nucleic acid sequences correspond to a plurality of different microsatellite loci and are obtained using a plurality of PCR primers configured to flank a plurality of microsatellite loci of a biological sample. When the PCR primers and the biological sample are combined and subjected to PCR amplification, fluorescently labeled DNA fragments are generated comprising the plurality of microsatellite loci. Fluorescent data obtained from the plurality of fluorescently labelled microsatellite loci are used to classify microsatellite instability of the biological sample.
Abstract:
Systems, primers, kits, and methods for detecting microsatellite instability in a biological sample are described. Signal data is received from a capillary electrophoresis genetic analysis instrument, wherein the signal data is measured from fluorescence of fragments comprising nucleic acid sequences amplified from the biological sample via polymerase chain reaction (PCR). The nucleic acid sequences correspond to a plurality of different microsatellite loci and are obtained using a plurality of PCR primers configured to flank a plurality of microsatellite loci of a biological sample. When the PCR primers and the biological sample are combined and subjected to PCR amplification, fluorescently labeled DNA fragments are generated comprising the plurality of microsatellite loci. Fluorescent data obtained from the plurality of fluorescently labelled microsatellite loci are used to classify microsatellite instability of the biological sample.
Abstract:
A system for analyzing biological data, comprising: a storage configured to store a plurality of data files containing biological data obtained from a plurality of devices; a server configured to: host a plurality of applications, each configured to be implemented on the server and to provide analysis, manipulation, comparison, visualization, or a combination thereof, of the biological data included in the data files, wherein the plurality of applications allow a user to analyze different data files related to the same sample and compare the results of the analysis.
Abstract:
In one exemplary embodiment, a computer-implemented method for determining a genetic result from a biological sample is provided. The method includes receiving nucleic acid amplification data of a biological sample, by a processor, from a biological instrument. The method further includes storing translation data, in a memory. The translation data includes a pattern of assay values associated with possible genetic results. The method further includes comparing the translation data with the nucleic acid amplification data, by the processor, to generate the genetic result of the biological sample. Moreover, the method includes displaying the genetic result, on a display, to a user.
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.