Abstract:
A method for validating an instrument is provided. The method includes receiving amplification data from a validation plate to generate a plurality of amplification curves (102, 202). The validation plate includes a sample of a first quantity and a second quantity, and each amplification curve includes an exponential region. The method further includes determining a set of fluorescence thresholds based on the exponential regions of the plurality of amplification curves (104, 204) and determining, for each fluorescence threshold of the set, a first set of cycle threshold (C t ) values of amplification curves generated from the samples of the first quantity and a second set of C t values of amplification curves generated from the samples of the second quantity (106, 206). The method includes calculating if the first and second quantities are sufficiently distinguishable based on C t values at each of the plurality of fluorescence thresholds (108, 208-218).
Abstract:
Embodiments implementing selected automated quality control operations in sample processing instruments and systems are disclosed. Embodiments for implementing automated correction of spectral error in such instruments and systems are also disclosed. These and other embodiments are further disclosed herein.
Abstract:
In one exemplary embodiment, a method for detecting variants in electropherogram data is provided. The method includes receiving electropherogram data from an instrument and analyzing the electropherogram data to identify mixed bases in the electropherogram data. The method further includes identifying features within the electropherogram data indicative of errors and validating the identified mixed bases. Then the method includes determining variants in the electropherogram data based on the validated mixed bases.
Abstract:
A method of automatically sequencing or basecalling one or more DNA (deoxyribonucleic acid) molecules of a biological sample is described. The method comprises using a capillary electrophoresis genetic analyzer to measure the biological sample to obtain at least one input trace comprising digital data corresponding to fluorescence values for a plurality of scans. Scan labelling probabilities for the plurality of scans are generated using a trained artificial neural network comprising a plurality of layers including convolutional layers. A basecall sequence comprising a plurality of basecalls for the one or more DNA molecules based on the scan labelling probabilities for the plurality of scans is determined.
Abstract:
A deep basecaller system for Sanger sequencing and associated methods are provided. The methods use deep machine learning. A Deep Learning Model is used to determine scan labelling probabilities based on an analyzed trace. A Neural Network is trained to learn the optimal mapping function to minimize a Connectionist Temporal Classification (CTC) Loss function. The CTC function is used to calculate loss by matching a target sequence and predicted scan labelling probabilities. A Decoder generates a sequence with the maximum probability. A Basecall position finder using prefix beam search is used to walk through CTC labelling probabilities to find a scan range and then the scan a position of peak labelling probability within the scan range for each called base. A Quality Value (QV) is determined using a feature vector calculated from CTC labelling probabilities as an index into a QV look-up table to find a quality score.
Abstract:
A biological analysis system and an associated method are provided. The method is used for recovering off scale data in an image produced by a camera in a capillary electrophoresis instrument. The method comprises the steps of identifying bins of the image where electron counts exceed a maximum number of counts; setting an off-scale flag for the identified bins; and processing the image to obtain a recovered dye signal, based on the flag set for each bin, and using a dye matrix.
Abstract:
Embodiments implementing selected automated quality control operations in sample processing instruments that analyze dye-labeled samples are disclosed. In some embodiments, temperature and/or pressure parameters are measured and compared to thresholds to determine whether warning should be provided and/or actions taken. Embodiments for implementing automated correction of spectral error during the instrument's normal runtime operation without requiring the user to conduct a special, separate calibration run are also disclosed.
Abstract:
In one exemplary embodiment, a method for calibrating an instrument is provided. The instrument includes an optical system capable of imaging florescence emission from a plurality of reaction sites. The method includes performing a region-of-interest (ROI) calibration to determine reaction site positions in an image. The method further includes performing a pure dye calibration to determine the contribution of a fluorescent dye used in each reaction site by comparing a raw spectrum of the fluorescent dye to a pure spectrum calibration data of the fluorescent dye. The method further includes performing an instrument normalization calibration to determine a filter normalization factor. The method includes performing an RNase P validation to validate the instrument is capable of distinguishing between two different quantities of sample.
Abstract:
A biological analysis system is provided. The system comprises a sample block assembly. The sample block assembly comprises a sample block configured to accommodate a sample holder, the sample holder configured to receive a plurality of samples. The system also comprises a control system configured to cycle the plurality of samples through a series of temperatures. The system further comprises an automated tray comprising a slide assembly, the tray configured to reversibly slide the sample block assembly from a closed to an open position to allow user access to the plurality of sample holders.
Abstract:
A biological analysis system is provided. The system comprises a sample block assembly. The sample block assembly comprises a sample block configured to accommodate a sample holder, the sample holder configured to receive a plurality of samples. The system also comprises a control system configured to cycle the plurality of samples through a series of temperatures. The system further comprises an automated tray comprising a slide assembly, the tray configured to reversibly slide the sample block assembly from a closed to an open position to allow user access to the plurality of sample holders.