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Researchers at the University of Illinois Urbana-Champae (University of Illinois urbana-champae) have developed a new computational tool that can use single nucleotide polymorphisms to identify pathways related to disease, including breast and prostate cancer
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SNPs refer to a person's DNA mutations and are the most common type of genetic variation in humans
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Saurabh Sinha (BSD/CABBI/GNDP/GSP), professor of computer science and director of IGB's computational genomics, said: "This work is part of the Mayo challenge to improve our understanding of left heart hypoplasia syndrome
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" This is a rare type of congenital heart disease in children, and there is currently no cure
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The tool is called VarSAn (Variant Set Annotator, pronounced "version"), and uses sequencing to study identified disease-related SNPs to predict which pathways may be interfered by these SNPs
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"We are trying to solve this problem from a computational perspective
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Do all the SNPs identified in genetic research point us to specific pathways that may not be known in the literature?" Sinha said
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The VarSAn tool was verified through two different methods
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The second method is based on testing the consistency of VarSAn's research results
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The team is now trying to make VarSAn an online tool where researchers can paste a list of SNPs and the tool directly reports the path
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"Currently, if users want to use this tool, they have to download the repository and run the code themselves, which may be very inconvenient
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This research was funded by the Mayo Clinic Center for Individualized Medicine, the Todd and Karen Warneck Left Heart Deformity Syndrome Project, and the National Institutes of Health
"VarSAn: associating pathways with a set of genomic variants using network analysis" was published inNucleic Acids Researchand can be found athttps://doi.