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D-GRIP : DNA genetic risk information profile : A genotype analysis system to predict a genetic risk profile for an individual

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Title: D-GRIP : DNA genetic risk information profile : A genotype analysis system to predict a genetic risk profile for an individual
Author: Srivastava, Siddhartha
Degree Master of Science - MSc
Program Bioinformatics
Copyright Date: 2007
Abstract: New genotyping technologies are producing reliable results with far greater coverage and at dramatically lower cost than previously possible. Given the rapid new discovery of disease associated markers and the new technology for determining the nucleotide sequences of key positions in the DNA of an individual, it is now feasible to apply existing knowledge to generate personalized analyses of genetic risk for diverse diseases. DNA Genetic Risk Information Profile (D-GRIP) is a genotype analysis software system that determines an individual's genetic risk profile given a genotype. The prototype web tool can take, as input, up to a million observed genotypes from single nucleotide positions known to be polymorphic in a human population. The submitted genotype data are compared to a database of disease associated single nucleotide polymorphisms (SNPs) and an output is generated, reporting disease-associated variants for which the individual has a predicted modified risk. An evaluation of D-GRIP was performed through the direct surveying of potential users of such a system - users such as clinicians, genetic counselors and genetics researchers. Due to ethical issues related to providing a genetic risk profile, the prototype system is kept closed to the general public and reserved for research into the utility and requirements of such software. The major conclusions drawn direct attention towards the key limitations presently precluding the creation of personalized genetic risk assessment. The lack of computationally exploitable resource for disease associated genetic variants, the inherent statistical complexities involved with risk calculation for large-scale genotyping data and the limited understanding of interactions between genes, environment and complex diseases, are all key factors that need to be overcome in order to create a practical genetic risk assessment tool.
URI: http://hdl.handle.net/2429/32186
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]
Scholarly Level: Graduate

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