Abstract: Monitoring, analysis and control of fermentation activities includes methods and corresponding systems directed toward agriculture, biofuels, and food production. Complex methods and corresponding systems are provided for classifying a microorganism; profiling a microbiome; sequencing multiple libraries in a single sequencing run; determining a microbiome profile in a sample; and analyzing a material from a location associated with a fermentation process. Additional implementations are directed to methods and corresponding systems for obtaining, deriving, predicting and evaluating microbiome information; control, analysis and direction of fermentation operations; and evaluating, analyzing and displaying microbiome related information in two and three dimensional plots. Yet additional methods and corresponding systems permit identification and analysis of microorganisms capable of imparting beneficial properties to phases of fermentation processes.

Abstract: A computer-implemented method and system for modifying a musculoskeletal model is provided. Test data for a set of ergonomic tests performed by a number of test subjects fitting a profile is obtained. A number of muscle parameters for a number of muscles in the musculoskeletal model are adjusted using the test data to modify the musculoskeletal model to adapt to the profile.

Abstract: Compositions, systems and methods for generating and using internal standard spike-in mixes including a combination of template spikes. Compositions, systems and methods described herein are directed to using the internal standard spike-in mixes to evaluate a set of workflow pipelines to perform differential abundance analyses on a sample containing variations of a target nucleic acid sequence of interest. Compositions, systems and methods described herein are directed to using the internal spike-in mixes to validate results obtained from differential abundance analyses performed on a sample containing variations of a target nucleic acid sequence of interest, where the variations may be of highly variable levels of relative abundance.

Abstract: Inferring a characteristic of an individual is disclosed. An indication that a first user and a second user have at least one shared chromosomal segment is received. Information about the second user is obtained. A characteristic of the first user is inferred based at least in part on the information about the second user.

Abstract: The present invention is directed to a method for generating a library of antigen binding molecules for screening for binding to an epitope of interest, said method comprising: a. selecting a template antigen-binding molecule from a set of possible template antigen binding molecules wherein said selected template does not specifically bind the epitope of interest but is known to specifically bind another epitope; b. selecting at least one residue position in said template antigen-binding molecule for mutation; and c. selecting at least one variant residue to substitute at the at least one residue position selected in b; such that a library containing a plurality of variants of said template is generated.

Abstract: The invention includes methods and systems for identifying diseased-induced mutations by producing multi-dimensional reference sequence constructs that account for variations between individuals, different diseases, and different stages of those diseases. Once constructed, these reference sequence constructs can be used to align sequence reads corresponding to genetic samples from patients suspected of having a disease, or who have had the disease and are in suspected remission. The reference sequence constructs also provide insight to the genetic progression of the disease.

Abstract: The invention provides methods for the use of gene expression measurements to classify or identify tumors in samples obtained from a subject in a clinical setting, such as in cases of formalin fixed, paraffin embedded (FFPE) samples.

Abstract: Disclosed herein are methods and systems for determining the numbers of targets. In some embodiments, the method comprise: stochastically barcoding targets using stochastic barcodes; obtaining sequencing data; for one or more of the targets: counting the number of molecular labels with distinct sequences associated with the target in the sequencing data; identifying clusters of molecular labels of the target using directional adjacency; collapsing the sequencing data using the clusters of molecular labels of the target identified; and estimating the number of the target.

Abstract: Contemplated systems and methods employ chimeric reference sequences that include a plurality of viral genome sequences to identify/quantify integration and co-amplification events. Most typically, the viral genome sequences are organized in the chimeric reference sequences as single chromosomes and the chimeric reference sequences are in BAM format.

Abstract: A system, computer program product, method and algorithm for evaluation of blood glucose variability—one of the most important parameters of diabetes management. An embodiment of the method may use routine self-monitoring blood glucose (SMBG) data collected over a period of 2-6 weeks, for example, based on a theory of risk analysis of blood glucose data. One aspect may include a method, system and computer program product for computing the Average Daily Risk Range (ADRR)—a measure of overall glucose variability. Another aspect may include a method, system, and computer program product for estimating separately the glucose variability in the hypoglycemic range via a Low BG Index (LBGI) and the glucose variability in the high BG range via High BG Index (HBGI) followed by a combination of the two indices into a single variability display.

Abstract: The present disclosure provides methods of determining one or more tissues and/or cell-types contributing to cell-free DNA (“cfDNA”) in a biological sample of a subject. In some embodiments, the present disclosure provides a method of identifying a disease or disorder in a subject as a function of one or more determined more tissues and/or cell-types contributing to cfDNA in a biological sample from the subject.

Abstract: The present invention relates to a method capable of, in order to diagnose fetal sex chromosome aneuploidy, differentiating Kleinfeiter's syndrome (XXY), triple X syndrome (XXX), and Turner's syndrome (monosomy X, XO) as well as male (XY) and female (XX) by using copy number variation (CNV). The differentiation method according to the present invention has significantly high sensitivity and accuracy since the reference line is evenly adjusted by performing normalization regardless of the kinds of platform and data. The present invention is useful in diagnosing the sex chromosome abnormality at an early stage through easy diagnosis of sex chromosomes X and Y, which are hard to diagnose, since an analysis is possible even with a small amount of fetal chromosomes, which corresponds to an advantage of noninvasive prenatal diagnosis, and copies are redundant.

Abstract: Various embodiments select markers for modeling epistasis effects. In one embodiment, a processor receives a set of genetic markers and a phenotype. A relevance score is determined with respect to the phenotype for each of the set of genetic markers. A threshold is set based on the relevance score of a genetic marker with a highest relevancy score. A relevance score is determined for at least one genetic marker in the set of genetic markers for at least one interaction between the at least one genetic marker and at least one other genetic marker in the set of genetic markers. The at least one interaction is added to a top-k feature set based on the relevance score of the at least one interaction satisfying the threshold.

Abstract: Identification of inheritance-by-descent haplotype matches between individuals is described. A set of tables including word match, haplotypes and segment match tables are populated. DNA samples are received and stored. A word identification module extracts haplotype values from each sample. The word match table is indexed according to the unique combination of position and haplotype. Each column represents a different sample, and each cell indicates whether that sample includes that haplotype at that position. The haplotypes table includes the raw haplotype data for each sample. The segment match table is indexed by sample identifier, and columns represent other samples. Each cell is populated to indicate for each identified sample pair which position range(s) include matching haplotypes for both samples. The tables are persistently stored in databases of the matching system. As new sample data is received, each table is updated to include the newly received samples, and additional matching takes place.

Abstract: Various embodiments select markers for modeling epistasis effects. In one embodiment, a processor receives a set of genetic markers and a phenotype. A relevance score is determined with respect to the phenotype for each of the set of genetic markers. A threshold is set based on the relevance score of a genetic marker with a highest relevancy score. A relevance score is determined for at least one genetic marker in the set of genetic markers for at least one interaction between the at least one genetic marker and at least one other genetic marker in the set of genetic markers. The at least one interaction is added to a top-k feature set based on the relevance score of the at least one interaction satisfying the threshold.

Abstract: Provided are methods for determining if a cannabis sample comprises hemp or marijuana, or Cannabis sativa and/or Cannabis indica as well as primers and kits for use in the methods.

Abstract: Systems and methods are disclosed to detect single-nucleotide variations (SNVs) from somatic sources in a cell-free biological sample of a subject by generating training data with class labels; in computer memory, generating a machine learning unit comprising one output for each of adenine (A), cytosine (C), guanine (G), and thymine (T) calls; training the machine learning unit; and applying the machine learning unit to detect the SNVs from somatic sources in the cell-free biological sample of the subject, wherein the cell-free biological sample comprises a mixture of nucleic acid molecules from somatic and germline sources.

Abstract: Disclosed herein are methods and systems for determining the numbers of targets. In some embodiments, the method comprise: stochastically barcoding targets using stochastic barcodes; obtaining sequencing data; for one or more of the targets: counting the number of molecular labels with distinct sequences associated with the target in the sequencing data; identifying clusters of molecular labels of the target using directional adjacency; collapsing the sequencing data using the clusters of molecular labels of the target identified; and estimating the number of the target.

Abstract: Disclosed herein are methods and systems that can reconstruct, extract, and/or analyze TCR sequences using short reads. The methods and systems can be applied to both single cell and bulk sequencing data.

Abstract: The present disclosure provides methods and systems for determining and/or characterizing one or more haplotypes and/or phasing of haplotypes in a nucleic acid sample. In particular, the disclosure provides methods for determining a haplotype and/or phasing of haplotypes in a nucleic acid sample by incorporating synthetic polymorphisms into fragments of a nucleic acid sample and utilizing the synthetic polymorphisms in determining one or more haplotypes and/or phasing of haplotypes.