Sparse genomic structural variant detection: Exploiting parent-child relatedness for signal recovery
Sparse genomic structural variant detection: Exploiting parent-child relatedness for signal recovery
复制标题
稀疏基因组结构变异检测：利用亲子相关性进行信号恢复
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Suzanne S. Sindi
中科院分区：
文献类型：
--
作者：
Mario Banuelos;R. Almanza;Lasith Adhikari;Roummel F. Marcia;Suzanne S. Sindi
结构变异(SVS)--个体基因组的重排--是人类和其他哺乳动物物种异质性的重要来源。通常，通过将测试基因组的DNA片段与已知的参考基因组进行比较来识别SVS，但测序和嘈杂的作图过程中的错误导致了高的假阳性率。当研究多个相关个体时，它们的关联性对改善真实SVS的信号提供了约束。我们开发了一种计算方法来预测给定的来自孩子和父母的基因组DNA的SVS。我们演示了加强个体之间的关联性并使用稀疏性提升ℓ1惩罚来约束我们的解决方案(因为SV实例应该很少)会导致性能的提高。我们介绍了来自1000基因组计划的模拟基因组以及两个测序的亲子三重序列的结果。
Structural variants (SVs) - rearrangements of an individuals' genome - are an important source of heterogeneity in human and other mammalian species. Typically, SVs are identified by comparing fragments of DNA from a test genome to a known reference genome, but errors in both the sequencing and the noisy mapping process contribute to high false positive rates. When multiple related individuals are studied, their relatedness offers a constraint to improve the signal of true SVs. We develop a computational method to predict SVs given genomic DNA from a child and both parents. We demonstrate that enforcing relatedness between individuals and constraining our solution with a sparsity-promoting ℓ1 penalty (since SV instances should be rare) results in improved performance. We present results on both simulated genomes as well as two-sequenced parent-child trios from the 1000 Genomes Project.
来自1,092个人基因组的遗传变异的综合图。
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
7
作者：
Quinlan, Aaron R.;Clark, Royden A.;Hall, Ira M.
通讯作者：
Hall, Ira M.