Title |
SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS
|
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Published in |
BMC Bioinformatics, January 2013
|
DOI | 10.1186/1471-2105-14-s1-s9 |
Pubmed ID | |
Authors |
Ivan Merelli, Andrea Calabria, Paolo Cozzi, Federica Viti, Ettore Mosca, Luciano Milanesi |
Abstract |
The capability of correlating specific genotypes with human diseases is a complex issue in spite of all advantages arisen from high-throughput technologies, such as Genome Wide Association Studies (GWAS). New tools for genetic variants interpretation and for Single Nucleotide Polymorphisms (SNPs) prioritization are actually needed. Given a list of the most relevant SNPs statistically associated to a specific pathology as result of a genotype study, a critical issue is the identification of genes that are effectively related to the disease by re-scoring the importance of the identified genetic variations. Vice versa, given a list of genes, it can be of great importance to predict which SNPs can be involved in the onset of a particular disease, in order to focus the research on their effects. |
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Psychology | 3 | 3% |
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