基于压缩序列的稀有等位基因检测
Rare-Allele Detection Using Compressed Se(que)nsing
摘要：
通过重测序检测罕见变异对于鉴定携带疾病变异的个体是重要的。新技术的快速测序使得靶区域的低成本重测序成为可能，尽管测试超过几个个体仍然是禁止的。为了改善成本权衡，最近有人建议应用汇集设计，其能够检测个体群体中的稀有等位基因的携带者。然而，这只适用于人才库中相对较少的个人，需要为特定情况设计人才库计划。我们提出了一种新的池化设计，基于压缩感知方法，这是通用的，简单的和有效的。我们对实验过程进行了建模，并通过计算机模拟表明，它能够从比以前更大的群体中回收稀有等位基因携带者，特别是在每个人都获得高覆盖率的情况下。我们的方法也可以与条形码技术相结合，以提高性能，并提供一个可行的解决方案，根据目前的重测序成本。例如，当靶向足够小的基因组区域（~100个碱基对）并且仅使用~10个测序泳道和~10个不同的条形码时，可以从超过4000个个体的群体中恢复4个稀有等位基因携带者的身份。
英文摘要：
Detection of rare variants by resequencing is important for the identification of individuals carrying disease variants. Rapid sequencing by new technologies enables low-cost resequencing of target regions, although it is still prohibitive to test more than a few individuals. In order to improve cost trade-offs, it has recently been suggested to apply pooling designs which enable the detection of carriers of rare alleles in groups of individuals. However, this was shown to hold only for a relatively low number of individuals in a pool, and requires the design of pooling schemes for particular cases. We propose a novel pooling design, based on a compressed sensing approach, which is both general, simple and efficient. We model the experimental procedure and show via computer simulations that it enables the recovery of rare allele carriers out of larger groups than were possible before, especially in situations where high coverage is obtained for each individual. Our approach can also be combined with barcoding techniques to enhance performance and provide a feasible solution based on current resequencing costs. For example, when targeting a small enough genomic region (~100 base-pairs) and using only ~10 sequencing lanes and ~10 distinct barcodes, one can recover the identity of 4 rare allele carriers out of a population of over 4000 individuals.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
