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Compressed Genotyping
IEEE Transactions on Information Theory ( IF 2.2 ) Pub Date : 2010-02-01 , DOI: 10.1109/tit.2009.2037043
Yaniv Erlich 1 , Assaf Gordon , Michael Brand , Gregory J Hannon , Partha P Mitra
Affiliation  

Over the past three decades we have steadily increased our knowledge on the genetic basis of many severe disorders. Nevertheless, there are still great challenges in applying this knowledge routinely in the clinic, mainly due to the relatively tedious and expensive process of genotyping. Since the genetic variations that underlie the disorders are relatively rare in the population, they can be thought of as a sparse signal. Using methods and ideas from compressed sensing and group testing, we have developed a cost-effective genotyping protocol to detect carriers for severe genetic disorders. In particular, we have adapted our scheme to a recently developed class of high throughput DNA sequencing technologies. The mathematical framework presented here has some important distinctions from the ¿traditional¿ compressed sensing and group testing frameworks in order to address biological and technical constraints of our setting.

中文翻译:

压缩基因分型

在过去的三十年中,我们稳步增加了对许多严重疾病的遗传基础的了解。尽管如此,在临床中常规应用这些知识仍然存在巨大挑战,主要是由于基因分型过程相对繁琐和昂贵。由于导致疾病的遗传变异在人群中相对罕见,因此可以将它们视为稀疏信号。使用来自压缩感知和群体测试的方法和想法,我们开发了一种具有成本效益的基因分型协议来检测严重遗传疾病的携带者。特别是,我们已将我们的方案调整为最近开发的一类高通量 DNA 测序技术。
更新日期:2010-02-01
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