Methods of selection, reporting and analysis of genetic markers using broad-based genetic profiling applications

Abstract

Disclosed is a method for determining whether an individual has an enhanced, diminished, or average probability of exhibiting one or more phenotypic attributes and related methods of selecting a set of genetic markers; for providing relevant genetic information to an individual; of evaluating the probability that progeny of two individuals of the opposite sex will exhibit one or more phenotypic attributes; and for determining the genomic ethnicity of an individual.

What is claimed is: 
     
         1 . A computer-implemented method for providing an evaluation for display on a computer generated report, which evaluation is with respect to identifying one or more genetic variants that are associated with a phenotype, comprising:
 (a) obtaining genomic markers from one or more genes or genomic regions of a biological sample of a subject, wherein said one or more genes or genomic regions include said one or more genetic variants;   (b) using computer software executed on a computer, evaluating said genomic markers from said subject for zygosity;   (c) comparing said zygosity of said genomic markers to a multivariate scoring matrix to obtain marker scores for said genomic markers, wherein said multivariate scoring matrix is algorithmically constructed and manipulated to relate patterns of genomic marker zygosity with measures of exhibiting phenotypes, including said phenotype, and wherein said measures are based at least in part on ontological relevance;   (d) prioritizing said genomic markers based on said marker scores; and   (e) providing said evaluation for display on a computer generated report that identifies said one or more genetic variants that contribute to said phenotype.   
     
     
         2 . The method of  claim 1 , wherein said ontological relevance is based on a description of a molecular function, biological process, or cellular component. 
     
     
         3 . The method of  claim 1 , wherein said ontological relevance is based on information about human disease. 
     
     
         4 . The method of  claim 1 , wherein said ontological relevance is based on databases comprising information about phenotypes attributed to mutated genes in non-human organisms. 
     
     
         5 . The method of  claim 1 , wherein said ontological relevance is based on databases comprising information about paralogous and homologous genes and phenotypes due to mutations in said paralogous and homologous genes in humans and other organisms. 
     
     
         6 . The method of  claim 1 , wherein said ontological relevance is determined by inferring synonyms of a semantic class by tracing a path between terms in one or more ontologies. 
     
     
         7 . The method of  claim 6 , wherein said ontological relevance is determined by propagating information across ontologies. 
     
     
         8 . The method of  claim 6 , wherein said one or more ontologies comprise Medical Subject Headings (MeSH), Gene Ontology (GO), Online Mendelian Inheritance of Man (OMIM), and Human Gene Mutation Data (HGMD). 
     
     
         9 . The method of  claim 1 , wherein said phenotype is a disease. 
     
     
         10 . The method of  claim 9 , wherein said disease is a common disease. 
     
     
         11 . The method of  claim 9 , wherein said disease is a rare disease. 
     
     
         12 . The method of  claim 1 , wherein said phenotype is drug metabolism. 
     
     
         13 . The method of  claim 1 , wherein said multivariate scoring matrix relates patterns of genomic marker zygosity with measures of exhibiting phenotypes based at least in part on medical physiological measures or values. 
     
     
         14 . The method of  claim 1 , wherein said genomic markers are preselected based on association or other studies to be directly or indirectly linked with a phenotypic attribute. 
     
     
         15 . The method of  claim 1 , wherein said genomic markers comprise both coding and non-coding variants. 
     
     
         16 . The method of  claim 1 , further comprising prioritizing said genomic markers by synteny with respect to other marker sequences. 
     
     
         17 . The method of  claim 1 , further comprising prioritizing said genomic markers with respect to genomic relevance. 
     
     
         18 . The method of  claim 17 , wherein said genomic relevance includes a characterization of said genomic markers based on at least one feature selected from the group consisting of codon position, codon changes, and functional characterization. 
     
     
         19 . The method of  claim 18 , wherein said functional characterization includes a missense mutation, non-sense mutation, exonic mutation, intronic mutation, 5′UTR mutation, 3′UTR mutation, upstream mutation, or downstream mutation. 
     
     
         20 . The method of  claim 1 , further comprising prioritizing said genomic markers with respect to quality of supporting research. 
     
     
         21 . The method of  claim 1 , further comprising prioritizing said genomic markers with respect to degree of phenotypic significance. 
     
     
         22 . The method of  claim 1 , further comprising evaluating said genomic markers at least in part based on population frequency. 
     
     
         23 . The method of  claim 1 , further comprising providing links to scientific literature on at least a subset of said genomic markers contributing to said phenotype. 
     
     
         24 . The method of  claim 1 , wherein said computer generated report is formatted according to an organizational matrix, wherein said organizational matrix determines said grouping and presentation of information presented in said computer generated report. 
     
     
         25 . The method of  claim 1 , further comprising performing assays to identify said genomic markers, wherein said assays are targeted to said one or more genes or genomic regions. 
     
     
         26 . The method of  claim 25 , wherein said assays include nucleic acid amplification or sequencing of said biological sample. 
     
     
         27 . The method of  claim 1 , wherein said computer generated report is provided for display on a graphical user interface. 
     
     
         28 . The method of  claim 1 , wherein said computer generated report is provided for display in a documentary format. 
     
     
         29 . The method of  claim 1 , wherein said multivariate scoring matrix comprises a combination of one or more scoring matrix vectors selected from said group consisting of a descriptor of family history, a descriptor of general medical physiological values, a descriptor of mRNA expression levels, a descriptor of methylation profiles, a descriptor of protein expression levels, a descriptor of enzyme activity, and a descriptor of antibody load. 
     
     
         30 . The method of  claim 1 , wherein said ontological relevance improves said prioritizing in (d) with respect to prioritization without use of ontological relevance.