Single Nucleotide Polymorphism (SNP) Detection and Genotype Calling from Massively Parallel Sequencing (MPS) Data.
Single Nucleotide Polymorphism (SNP) Detection and Genotype Calling from Massively Parallel Sequencing (MPS) Data.
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DOI：
10.1007/s12561-012-9067-4
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发表时间：
2013-05
影响因子：
1
通讯作者：
Zhou, Yi-Hui
中科院分区：
文献类型：
--
作者：
Li, Yun;Chen, Wei;Liu, Eric Yi;Zhou, Yi-Hui
大规模平行测序（MPS）自2005年问世以来，已经改变了基因组研究领域。这些新的测序技术已经成功地鉴定了几种罕见孟德尔疾病的因果变异。他们也开始兑现自己的承诺，解释一些复杂性状的全基因组关联研究（GWAS）中缺失的遗传性。我们预计在不久的将来，基于mps的研究将迅速增加，用于各种应用。一个至关重要且几乎不可避免的步骤是检测snp并从测序数据中调用检测到的多态性位点的基因型。在这里，我们回顾了过去五年中为此目的提出的统计方法。此外，我们还讨论了与SNP检测和MPS数据的基因型调用相关的新问题和未来方向。
Massively parallel sequencing (MPS), since its debut in 2005, has transformed the field of genomic studies. These new sequencing technologies have resulted in the successful identification of causal variants for several rare Mendelian disorders. They have also begun to deliver on their promise to explain some of the missing heritability from genome-wide association studies (GWAS) of complex traits. We anticipate a rapidly growing number of MPS-based studies for a diverse range of applications in the near future. One crucial and nearly inevitable step is to detect SNPs and call genotypes at the detected polymorphic sites from the sequencing data. Here, we review statistical methods that have been proposed in the past five years for this purpose. In addition, we discuss emerging issues and future directions related to SNP detection and genotype calling from MPS data.