Abstract: Disclosed are methods for detecting and/or prioritizing phenotype-causing genomic variants and related software tools. The methods include genomic feature based analysis and can combine variant frequency information with sequence characteristics such as amino acid substation. The methods disclosed are useful in any genomics study; for example, rare and common disease gene discovery, tumor growth mutation detection, personalized medicine, agricultural analysis, and centennial analysis.

Abstract: Described herein are methods of identifying a plurality of polynucleotides, as well as detecting presence, absence, or abundance of a plurality of taxa in a sample. Also provided are systems for performing methods of the disclosure.

Abstract: A method for facilitating rapid genome sequence analysis includes accessing an output stream of an alignment process that includes aligned reads of a biological sequence that are aligned to a reference genome. The method also includes distributing the aligned reads to a plurality of computing nodes based on genomic position. Each of the plurality of computing nodes is assigned to a separate data bin of a plurality of data bins associated with genomic position. The method also includes, for at least one aligned read determined to overlap separate data bins of the plurality of data bins, duplicating the at least one aligned read and distributing the at least one aligned read to separate computing nodes of the plurality of computing nodes that are assigned to the separate data bins.

Abstract: Provided are methods for identifying gene variants associated with a phenotype, for example by inferring and scoring of structural variants from whole-genome or exome data or processing a set of genes against a known set of genes having known variants associated with a set of phenotypes, and optionally determining how likely each of the genes are to cause the phenotype.

Abstract: The present disclosure provides methods and systems for prioritizing phenotype-causing genomic variants. The methods include using variant prioritization analyses and in combination with biomedical ontologies using a sophisticated re-ranking methodology to re-rank these variants based on phenotype information. The methods can be useful in any genomics study and diagnostics; for example, rare and common disease gene discovery, tumor growth mutation detection, drug responder studies, metabolic studies, personalized medicine, agricultural analysis, and centennial analysis.

Abstract: Described herein are methods of identifying a plurality of polynucleotides, as well as detecting presence, absence, or abundance of a plurality of taxa in a sample. Also provided are systems for performing methods of the disclosure.

Abstract: Disclosed are methods for detecting and/or prioritizing phenotype-causing genomic variants and related software tools. The methods include genomic feature based analysis and can combine variant frequency information with sequence characteristics such as amino acid substation. The methods disclosed are useful in any genomics study; for example, rare and common disease gene discovery, tumor growth mutation detection, personalized medicine, agricultural analysis, and centennial analysis.

Abstract: Disclosed herein are analytical methods to predict or determine a subject's phenotype burden and/or genomic load from the subject's genome sequence variants. The disclosed methods may report a dynamically ordered list of genes or genomic regions responsible for each of one or more phenotypes. Also disclosed herein are analytical methods to convert the phenotype burden and/or genomic load into a probability or risk profile or percentile for a certain phenotype or one or more phenotypes among a plurality of phenotypes, which may be compared to a reference population.

Abstract: The present disclosure provides methods and systems for reprioritizing a first set of strings based on at least a node annotation to generate a second set of strings. One or more graphical representations comprising machine readable data in annotated nodes may be used to score a first set of strings. To score a first set of strings based on one or more node annotations, a seed node may be selected based on a node annotation corresponding to the first set of strings and a first value may be assigned to the seed node. Information may be propagated from a seed node to neighboring nodes and second values may be assigned to neighboring nodes. A score may be generated from at least a first value and a second value.

Abstract: Described herein are methods of identifying a plurality of polynucleotides, as well as detecting presence, absence, or abundance of a plurality of taxa in a sample. Also provided are systems for performing methods of the disclosure.

Abstract: The present disclosure provides methods and systems for prioritizing phenotype-causing genomic variants. The methods include using variant prioritization analyses and in combination with biomedical ontologies using a sophisticated re-ranking methodology to re-rank these variants based on phenotype information. The methods can be useful in any genomics study and diagnostics; for example, rare and common disease gene discovery, tumor growth mutation detection, drug responder studies, metabolic studies, personalized medicine, agricultural analysis, and centennial analysis.

Abstract: Disclosed are methods for detecting and/or prioritizing phenotype-causing genomic variants and related software tools. The methods include genomic feature based analysis and can combine variant frequency information with sequence characteristics such as amino acid substation. The methods disclosed are useful in any genomics study; for example, rare and common disease gene discovery, tumor growth mutation detection, personalized medicine, agricultural analysis, and centennial analysis.

Abstract: A hypothesis generation system includes a related concepts datastore recording relationships between core concepts in a field of study. A recognition module performs automatic recognition of a hypothesis recognition pattern respective of contents of the related concepts datastore. The recognition module records a hypothetical relationship between core concepts of the datastore based on recognition of the pattern.

Abstract: A literature pipeline corresponds to a document navigation system having a datastore of direct links between pre-defined core concepts found in a document corpus. A link identification module identifies indirect links between core concepts selected by a user based on connection of direct links through at least one core concept not selected by the user. An output communicates identified links to the user.