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10.1038/gim.2014.202

http://scihub22266oqcxt.onion/10.1038/gim.2014.202
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C4861313!4861313!25590976
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suck abstract from ncbi

pmid25590976      Genet+Med 2015 ; 17 (11): 859-65
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  • Symptom-driven idiopathic disease gene identification #MMPMID25590976
  • Molparia B; Pham PH; Torkamani A
  • Genet Med 2015[Nov]; 17 (11): 859-65 PMID25590976show ga
  • Purpose: Rare genetic variants are the major cause of Mendelian disorders, yet only half of described genetic diseases have been causally linked to a gene. In addition, the total number of rare genetic diseases is projected to be far greater than that of those already described. Whole-genome sequencing of patients with subsequent genetic and functional analysis is a powerful way to describe these gene anomalies. However, this approach results in tens to hundreds of candidate disease-causative genes, and the identification of additional individuals suffering from the same disorder can be difficult because of rarity and phenotypic heterogeneity. Methods: We describe a genetic network?based method to rank candidate genes identified in family-based sequencing studies, termed phenotype informed network (PIN) ranking. Furthermore, we present a case study as an extension of the PIN ranking method in which disease symptoms drive the network ranking and identification of the disease-causative gene. Results: We demonstrate, through simulation, that our method is capable of identifying the correct disease-causative gene in a majority of cases. PIN-rank is available at https://genomics.scripps.edu/pin-rank/. Conclusion: We have developed a method to prioritize candidate disease-causative genes based on symptoms that would be useful for both the prioritization of candidates and the identification of additional subjects.
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