De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm

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• 作者：Varun Aggarwala ; Arupa Ganguly ; Benjamin F. Voight
• 关键词：Mutation Rate ; Retinoblastoma ; de novo mutations ; Variability in Mutation Rate ; Variant Prioritization
• 刊名：BMC Genomics
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：18
• 期：1
• 全文大小：1169KB
• 刊物主题：Life Sciences, general; Microarrays; Proteomics; Animal Genetics and Genomics; Microbial Genetics and Genomics; Plant Genetics & Genomics;
• 出版者：BioMed Central
• ISSN：1471-2164
• 卷排序：18

文摘

BackgroundStudies of de novo mutations offer great promise to improve our understanding of human disease. After a causal gene has been identified, it is natural to hypothesize that disease relevant mutations accumulate within a sub-sequence of the gene – for example, an exon, a protein domain, or at CpG sites. These assessments are typically qualitative, because we lack methodology to assess the statistical significance of sub-gene mutational burden ultimately to infer disease-relevant biology.