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   HDR: a statistical two-step approach successfully identifies disease genes in autosomal recessive families  
   
نویسنده Imai Atsuko ,Kohda Masakazu ,Nakaya Akihiro ,Sakata Yasushi ,Murayama Kei ,Ohtake Akira ,Lathrop Mark ,Okazaki Yasushi ,Ott Jurg
منبع journal of human genetics - 2016 - دوره : 61 - شماره : 11 - صفحه:959 -963
چکیده    In the search for sequence variants underlying disease, commonly applied filtering steps usually result in a number of candidate variants that cannot further be narrowed down. in autosomal recessive families, disease usually occurs only in one generation so that genetic linkage analysis is unlikely to help. because homozygous recessive mutations tend to be inherited together with flanking homozygous variants, we developed a statistical method to detect pathogenic variants in autosomal recessive families: we look for differences in patterns of homozygosity around candidate variants between patients and control individuals and expect that such differences are greater for pathogenic variants than random candidate variants. in six autosomal recessive mitochondrial disease families, in which pathogenic homozygous variants have already been identified, our approach succeeded in prioritizing pathogenic mutations. our method is applicable to single patients from recessive families with at least a few dozen control individuals from the same population; it is easy to use and is highly effective for detecting causative mutations in autosomal recessive families.
آدرس Osaka University Graduate School of Medicine, Department of Cardiovascular Medicine, Department of Genome Informatics, Japan. Rockefeller University, Laboratory of Statistical Genetics, USA. McGill University and Genome Québec Innovation Centre, Canada, Saitama Medical University, Division of Translational Research, Japan, Osaka University Graduate School of Medicine, Department of Genome Informatics, Japan, Osaka University Graduate School of Medicine, Department of Cardiovascular Medicine, Japan, Chiba Children’s Hospital, Department of Metabolism, Japan, Saitama Medical University, Department of Pediatrics, Japan, McGill University and Genome Québec Innovation Centre, Canada, Saitama Medical University, Division of Translational Research, Division of Functional Genomics & Systems Medicine, Japan, Rockefeller University, Laboratory of Statistical Genetics, USA. Chinese Academy of Sciences, China
 
     
   
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