Oxford Genome - Wide Association Software Suite - Isis Project No 3507, 3589, 3591, 3592

A world-leading suite of software for the statistical analysis of genetic information is available to license by commercial organisations

Marketing Opportunity

A number of differences in peoples’ genomes, termed single nucleotide polymorphisms or SNPs, have been associated with disease.  For example, certain SNPs in the DNA repair gene BRCA1 are very highly associated with breast cancer.  The majority of diseases for which there is a genetic component, however, are not associated with one particular genetic mutation, but alterations in a number of genes across the whole genome. Genome-wide association studies (GWAS) are beginning to elucidate these complex interactions, with at least 165 associations now known.  This represents a huge range of new drug targets, validated in humans, with the promise of many more as more GWAS are performed.

A world-leading team in Oxford have developed a range of programmes for statistical analysis of genome-wide data using novel algorithms. The programmes allow the user to gain an understanding of the complex interrelationships between many genetic variants and diseases and the conditions with which they are associated.  Reliable methods for analysing genome-wide data to understand these complexities have long been desired by geneticists in industry and academia alike. The Oxford Genome Analysis Software Suite has already elicited great interest from both academic groups and industry and we are now able to offer commercial licenses to this leading suite, in whole or in part.

The Oxford Genome-wide Analysis Software Suite (OGWASS)

3507: CHIAMO: This programme incorporates a novel algorithm for calling of overall genotypes from SNP intensity data. Further, it allows calling of genotypes in multiple cohorts at once using a hierarchical model. To our knowledge, this is a unique benefit.

3589: SNPTEST detects disease associations at SNPs in genetic studies and enables genotype uncertainty (a by-product of imputation – see below) to be taken into account.

3590: GTOOL: A program for converting genetic data between different file formats and for creating subsets of a given dataset. Our new algorithms use a new data format that allows genotypes to be stored with uncertainty. This is the only program that can convert data from and into this new format.

3591: IMPUTE: A novel algorithm for imputation/prediction of unobserved and missing SNP alleles in a dataset consisting of genotype data on a set of individuals based upon a panel of known haplotype data and a recombination map. The idea of imputing alleles has now become very popular in genetics studies of human disease and is being used to enable researchers to find new disease genes and share data. IMPUTE allows more precise and efficient prediction than other algorithms available.

3592: HAPGEN simulates case control datasets at linked SNP markers, conditional upon a set of known haplotypes based upon known panels of genetic variation.

3871: HAPQUEST: A program for haplotype phase inference which specifically takes into account a known set of haplotypes to improve the haplotype estimation.

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