Abstract: The invention relates to the selection of a collection of relevant single nucleotide polymorphisms across a genome to design a nucleic acid probe array. As such, the invention relates to diverse fields impacted by the nature of genetics, including biology, medicine, and medical diagnostics.

Abstract: The invention relates to the selection of a collection of relevant single nucleotide polymorphisms across a genome to design a nucleic acid probe array. As such, the invention relates to diverse fields impacted by the nature of genetics, including biology, medicine, and medical diagnostics.

Abstract: Methods, kits and arrays of nucleic acid probes for genotyping large numbers of human SNPs in parallel are provided. A set of more than 100,000 human SNPs, known to be biallelic in at least two populations is provided. Allele specific perfect match probes and genotyping probe sets are provided for each allele of each biallelic SNP in a set of human SNPs that is useful for genetic analysis within and across populations. Probe sets that include perfect match and mismatch probes are provided. The probe sets are suitable for inclusion in an array. The invention provides the SNP and surrounding sequence and provides the sequences in such a way as to make them available for a variety of analyses including genotyping. As such, the invention relates to diverse fields impacted by the nature of genetics, including biology, medicine, and medical diagnostics.

Abstract: Methods and computer software products are provided for analyzing gene expression data. In one embodiment, methods, systems and computer software are provided for comparative gene expression analysis using intensity dependent normalization factors.

Abstract: The invention relates to the selection of a collection of relevant single nucleotide polymorphisms across a genome to design a nucleic acid probe array. As such, the invention relates to diverse fields impacted by the nature of genetics, including biology, medicine, and medical diagnostics.

Abstract: In one aspect of the invention, methods, systems and computer software products are provided for analyzing genotyping data. In exemplary embodiment, genotype data are analyzed using a model based classification method.

Abstract: Methods and computer software products are provided for analyzing gene expression data. In one embodiment, methods, systems and computer software are provided for comparative gene expression analysis using intensity dependent normalization factors.

Abstract: Methods, kits and arrays of nucleic acid probes for genotyping large numbers of human SNPs in parallel are provided. A set of more than 100,000 human SNPs, known to be biallelic in at least two populations is provided. Allele specific perfect match probes and genotyping probe sets are provided for each allele of each biallelic SNP in a set of human SNPs that is useful for genetic analysis within and across populations. Probe sets that include perfect match and mismatch probes are provided. The probe sets are suitable for inclusion in an array. The invention provides the SNP and surrounding sequence and provides the sequences in such a way as to make them available for a variety of analyses including genotyping. As such, the invention relates to diverse fields impacted by the nature of genetics, including biology, medicine, and medical diagnostics.

Abstract: An embodiment of a method for calling the genotype of a biological sequence is described that comprises receiving sets of intensity data each comprising an intensity value for each probe feature associated with a probe set disposed on a probe array; independently applying filters to the intensity values of a probe set associated with a forward strand and of a probe set associated with a reverse strand, where the probe sets interrogate the same sequence position; independently applying models to the filtered intensity values for the forward strand and the reverse strand, where the models produce a genotype call for each strand; combining the genotype call for the forward strand and the genotype call for the reverse strand to generate a final genotype call; and testing the reliability of the final genotype call.

Abstract: A method for calling the genotype of a sample is described comprising the acts of receiving emission data for one or more target sequences each hybridized to a plurality of probe sets, where each of the probe sets comprises a plurality of probe features; calculating a set of values for each of the probe sets associated with each target sequence; selecting one of the set of values for each of the probe sets associated with each target sequence, wherein the value is selected if it is greater than a reference value; determining a significance value from the selected values of all the probe sets associated with each target sequence; and producing a genotype call for each target sequence based upon the significance value.

Abstract: In one aspect of the invention, methods, systems and computer software products are provided for analyzing genotyping data. In exemplary embodiment, genotype data are analyzed using a model based classification method.

Abstract: A system is described that associates grids with a probe array image based upon a positional placement of one or more control features, aligns the grids with one or more pixels based upon a metric value determined by one or more characteristics of the one or more pixels, and generates cell intensity values. The system may also associate grids with a probe array image based upon a positional placement of one or more control features, determine a ratio of pixel intensity values associated with areas of the grid and adjust the positional association of the grid based upon the determined ratio. The system may also associate grids with a probe array image based upon a positional placement of one or more control features and generate cell intensity values based upon weighted pixel intensity values associated with areas of the grid.

Abstract: Methods and computer software products are provided for analyzing gene expression data. In one embodiment, methods, systems and computer software are provided for comparative gene expression analysis using intensity dependent normalization factors.