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10.1002/humu.23160 http://scihub22266oqcxt.onion/10.1002/humu.23160 C5324660!5324660 !28008688     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28008688 &cmd=llinks): Failed to open stream: HTTP request failed! 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The Clinical Next-Generation Sequencing Database: A Tool for the Unified Management of Clinical Information and Genetic Variants to Accelerate Variant Pathogenicity Classification |pdf=|usr=}}{{28008688 }} gab.com Text The Clinical Next-Generation Sequencing Database: A Tool for the Unified Management of Clinical Information and Genetic Variants to Accelerate Variant Pathogenicity Classification JO: Hum Mutat http://www.kidney.de/pget.php?&tw=1&pmid=28008688 #FOAvip Recent advances in next-generation sequencing (NGS) have given rise to new challenges due to the difficulties in variant pathogenicity interpretation and large dataset management, including many kinds of public population databases as well as public or commercial disease-specific databases. Here, we report a new database development tool, named the "Clinical NGS Database," for improving clinical NGS workflow through the unified management of variant information and clinical information. This database software offers a two-feature approach to variant pathogenicity classification. The first of these approaches is a phenotype similarity-based approach. This database allows the easy comparison of the detailed phenotype of each patient with the average phenotype of the same gene mutation at the variant or gene level. It is also possible to browse patients with the same gene mutation quickly. The other approach is a statistical approach to variant pathogenicity classification based on the use of the odds ratio for comparisons between the case and the control for each inheritance mode (families with apparently autosomal dominant inheritance vs. control, and families with apparently autosomal recessive inheritance vs. control). A number of case studies are also presented to illustrate the utility of this database. Twit Text FOAVip The Clinical Next-Generation Sequencing Database: A Tool for the Unified Management of Clinical Information and Genetic Variants to Accelerate Variant Pathogenicity Classification ????Hum Mutat http://www.kidney.de/pget.php?&tw=1&pmid=28008688 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28008688 #FOAvip English Wikipedia <ref>{{Cite pmid|28008688 }}</ref> The Clinical Next-Generation Sequencing Database: A Tool for the Unified Management of Clinical Information and Genetic Variants to Accelerate Variant Pathogenicity Classification #MMPMID28008688 Nishio SY ; Usami SI Hum Mutat 2017[Mar]; 38 (3 ): 252-259 PMID28008688 show ga Recent advances in next-generation sequencing (NGS) have given rise to new challenges due to the difficulties in variant pathogenicity interpretation and large dataset management, including many kinds of public population databases as well as public or commercial disease-specific databases. Here, we report a new database development tool, named the "Clinical NGS Database," for improving clinical NGS workflow through the unified management of variant information and clinical information. This database software offers a two-feature approach to variant pathogenicity classification. The first of these approaches is a phenotype similarity-based approach. This database allows the easy comparison of the detailed phenotype of each patient with the average phenotype of the same gene mutation at the variant or gene level. It is also possible to browse patients with the same gene mutation quickly. The other approach is a statistical approach to variant pathogenicity classification based on the use of the odds ratio for comparisons between the case and the control for each inheritance mode (families with apparently autosomal dominant inheritance vs. control, and families with apparently autosomal recessive inheritance vs. control). A number of case studies are also presented to illustrate the utility of this database. |*Databases, Genetic [MESH] |*Genetic Predisposition to Disease [MESH] |*Genetic Variation [MESH] |*High-Throughput Nucleotide Sequencing [MESH] |Child [MESH] |Computational Biology/*methods [MESH] |Female [MESH] |Genetic Association Studies/*methods [MESH] |Humans [MESH] |Male [MESH] |Middle Aged [MESH] |Software [MESH] |User-Computer Interface [MESH]The Clinical Next-Generation Sequencing Database: A Tool for the Unifi(epmc).pdf DeepDyve Pubget Overpricing