Abstract: An input sample SNP genotype is divided into a plurality of windows, each including a sequence of SNPs. For each window, a diploid hidden Markov Model (HMM) is built and from a haplotype Markov Model (MM). The diploid HMM for a window is used to determine the probability that the window corresponds to a pair of labels (e.g., ethnicity labels). An inter-window HMM, with a set of states for each window, is built based on the diploid HMMs for each window. Labels are assigned to the input sample genotype based on the inter-window HMM.

Abstract: A computer system is provided for determining the relative effectiveness of anti-cancer drugs. The interface has selectable options, including an option to manage drug testing parameters, and enables user selection of desired drug testing parameters in relation to a virtual well plate associated with a physical well plate of a spectrophotometer. The computer system causes the spectrophotometer to start a drug test, wherein the physical well plate includes at least one test well containing viable cancer cells; and at least one drug candidate in a predetermined concentration; and at least one control well containing the viable cancer cells alone. The system records the optical density of the well at a predetermined wavelength at selected time intervals for a selected duration of time, and stores the optical density and time measurements in the database.

Abstract: Embodiments of the present invention provide methods, systems, and apparatus for deducing the fetal DNA fraction in maternal plasma without using paternal or fetal genotypes. Maternal genotype information may be obtained from a maternal-only DNA sample or may be assumed from shallow-depth sequencing of a biological sample having both maternal and fetal DNA molecules. Because sequencing may be at shallow depths, a locus may have only few reads and may fail to exhibit a non-maternal allele even if a non-maternal allele is present. However, normalized parameters that characterize non-maternal alleles sequenced can be used to provide an accurate estimate of the fetal DNA fraction, even if the amount of non-maternal alleles is in error. Methods described herein may not need high-depth sequencing or enrichment of specific regions. As a result, these methods can be integrated into widely used non-invasive prenatal testing and other diagnostics.

Abstract: A system and method for determining the immune status or immune cycle in a subject is provided. A sampling component for obtaining physiological data from the subject is provided together with a data storage component for storing the physiological data obtained from the subject. A processing component is provided to analyse the physiological data and thereby determine the immune status or periodicity of the immune cycle and the immune cycle of the subject. An output component for outputting the immune status or periodicity of the immune cycle, and the immune cycle of the subject and/or the future status or immune cycle of the subject is provided.

Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

Abstract: An input genotype is divided into a plurality of windows, each including a sequence of SNPs. For each window, a diploid HMM is computed based on genotypes and/or phased haplotypes to determine a probability of a haplotype sequence being associated with a particular label. For example, the diploid HMM for a window is used to determine the emission probability that the window corresponds to a set of labels. An inter-window HMM, with a set of states for each window, is computed. Labels are assigned to the input genotype based on the inter-window HMM. Upper and lower bounds are estimated to produce a range of likely percentage values an input can be assigned to a given label. Confidence values are determined indicating a likelihood that an individual inherits DNA from a certain population. Maps are generated with polygons representing regions where a measure of ethnicity of population falls within specific ranges.

Abstract: The invention provides methods and system for making specific base calls at specific loci using a reference sequence construct, e.g., a directed acyclic graph (DAG) that represents known variants at each locus of the genome. Because the sequence reads are aligned to the DAG during alignment, the subsequent step of comparing a mutation, vis-a-vis the reference genome, to a table of known mutations can be eliminated. The disclosed methods and systems are notably efficient in dealing with structural variations within a genome or mutations that are within a structural variation.

Abstract: Methods of deconvolving a feature profile of a physical system are provided herein. The present method may include: optimizing a regression between a) a feature profile of a first plurality of distinct components and b) a reference matrix of feature signatures for a second plurality of distinct components, wherein the feature profile is modeled as a linear combination of the reference matrix, and wherein the optimizing includes solving a set of regression coefficients of the regression, wherein the solution minimizes 1) a linear loss function and 2) an L2-norm penalty function; and estimating the fractional representation of one or more distinct components among the second plurality of distinct components present in the sample based on the set of regression coefficients. Systems and computer readable media for performing the subject methods are also provided.

Abstract: The present disclosure provides methods for determining the ploidy status of a chromosome in a gestating fetus from genotypic data measured from a mixed sample of DNA comprising DNA from both the mother of the fetus and from the fetus, and optionally from genotypic data from the mother and father. The ploidy state is determined by using a joint distribution model to create a plurality of expected allele distributions for different possible fetal ploidy states given the parental genotypic data, and comparing the expected allelic distributions to the pattern of measured allelic distributions measured in the mixed sample, and choosing the ploidy state whose expected allelic distribution pattern most closely matches the observed allelic distribution pattern. The mixed sample of DNA may be preferentially enriched at a plurality of polymorphic loci in a way that minimizes the allelic bias, for example using massively multiplexed targeted PCR.

Abstract: Cancer types (e.g., organ/tissue of origin and/or cancer subtype for an organ/tissue) can be distinguished by applying statistical methods to data samples consisting of counts of somatic single nucleotide variations (SNVs) across a tumor genome of a patient. For example, a factor loading matrix for each cancer type to be distinguished can be computed using a set of training data samples for which the cancer type is known. To determine the cancer type for a testing (or diagnostic) data sample, a regression analysis over the set of factor loading matrices yields statistical parameters that can be used to identify the cancer type.

Abstract: The present invention relates to genomic informatics and gene-expression profiling. Gene-expression profiles provide complex molecular fingerprints regarding the relative state of a cell or tissue. Similarities in gene-expression profiles between organic states provide molecular taxonomies, classification, and diagnostics. Similarities in gene-expression profiles resulting from various external perturbations reveal functional similarities between these perturbagens, of value in pathway and mechanism-of-action elucidation. Similarities in gene-expression profiles between organic and induced states may identify clinically-effective therapies. Systems and methods herein provide for the measurement of relative gene abundances, including unbiased selection of and construction of probes and targets designed and methods for using known properties of sparsity of measurements to reach gene abundances.

Abstract: A biosensor system determines analyte concentration from an output signal generated from a light-identifiable species or a redox reaction of the analyte. The biosensor system compensates at least 50% of the total error in the output signal with a primary function and compensates a portion of the remaining error with a residual function. The amount of error compensation provided by the primary and residual functions may be adjusted with a weighing coefficient. The compensation method including a primary function and a residual function may be used to determine analyte concentrations having improved accuracy from output signals including components attributable to error.

Abstract: Methods are provided for diagnosing pregnancy-associated disorders, determining allelic ratios, determining maternal or fetal contributions to circulating transcripts, and/or identifying maternal or fetal markers using a sample from a pregnant female subject. Also provided is use of a gene for diagnosing a pregnancy-associated disorder in a pregnant female subject.

Abstract: Described herein are systems and methods that receive as input a DNA or RNA sequence, extract features, and apply layers of processing units to compute one ore more condition-specific cell variables, corresponding to cellular quantities measured under different conditions. The system may be applied to a sequence containing a genetic variant, and also to a corresponding reference sequence to determine how much the condition-specific cell variables change because of the variant. The change in the condition-specific cell variables are used to compute a score for how deleterious a variant is, to classify a variant's level of deleteriousness, to prioritize variants for subsequent processing, and to compare a test variant to variants of known deleteriousness.

Abstract: In various embodiments, the present description relates to the use of factors related to survival. The methods, compositions and systems described herein may be used to determine factors affecting survival, assess survival risk based on factors related to survival and/or make suggestions to increase the likelihood of survival longer than otherwise predicted.

Abstract: Digital imagery can help to quantify seasonal changes in desirable crop phenotypes that can be treated as quantitative traits. Because limitations in precise and functional phenotyping restrain genetic improvement in the post-genomic era, imagery-based phenomics could become the next breakthrough to accelerate genetic gains in field crops. Whereas many phenomic studies focus on exploratory analysis of spectral data without obvious interpretative value, we used field images to directly measure soybean canopy development from phenological stage V2 to R5. Over three years, we collected imagery using ground and aerial platforms of a large and diverse nested association panel comprising 5,555 lines. Genome-wide association analysis of canopy coverage across sampling dates detected a large quantitative trait locus on soybean (Glycine max, L. Merr.) chromosome 19. This QTL provided an increase in yield of 47.3 kg·ha?1.

Abstract: Methods of deconvolving a feature profile of a physical system are provided herein. The present method may include: optimizing a regression between a) a feature profile of a first plurality of distinct components and b) a reference matrix of feature signatures for a second plurality of distinct components, wherein the feature profile is modeled as a linear combination of the reference matrix, and wherein the optimizing includes solving a set of regression coefficients of the regression, wherein the solution minimizes 1) a linear loss function and 2) an L2-norm penalty function; and estimating the fractional representation of one or more distinct components among the second plurality of distinct components present in the sample based on the set of regression coefficients. Systems and computer readable media for performing the subject methods are also provided.

Abstract: The technology disclosed relates to constructing a convolutional neural network-based classifier for variant classification. In particular, it relates to training a convolutional neural network-based classifier on training data using a backpropagation-based gradient update technique that progressively match outputs of the convolutional neural network-based classifier with corresponding ground truth labels. The convolutional neural network-based classifier comprises groups of residual blocks, each group of residual blocks is parameterized by a number of convolution filters in the residual blocks, a convolution window size of the residual blocks, and an atrous convolution rate of the residual blocks, the size of convolution window varies between groups of residual blocks, the atrous convolution rate varies between groups of residual blocks. The training data includes benign training examples and pathogenic training examples of translated sequence pairs generated from benign variants and pathogenic variants.

Abstract: The compositions and methods provided herein allow for identification of causative genetic biomarkers for a disease condition or drug response.

Abstract: As described below, disclosed herein are methods of analyzing DNA methylation in cell-free DNA (cfDNA) and genomic DNA (gDNA) from sequencing data.