SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data
SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data
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DOI：
10.1093/bioinformatics/btv449
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发表时间：
2015-11-15
期刊：
影响因子：
5.8
通讯作者：
Hughes, Austin L.
中科院分区：
文献类型：
--
作者：
Nelson, Chase W.;Moncla, Louise H.;Hughes, Austin L.
下一代测序技术的新应用使用来自多个个体的DNA池来估计群体遗传参数。然而，没有公开可用的工具来分析单核苷酸多态性（SNP）的调用结果直接为重要的进化参数在检测自然选择，包括核苷酸多样性和基因多样性。我们开发了SNPGenie来填补这一空白。用户提交FASTA参考序列、具有CDS信息的基因转移格式（.GTF）文件和格式选择不断增加的SNP报告。该程序估计核苷酸多样性、与参考的距离和基因多样性。标记多个重叠阅读框的位点，并按多态性类型分类：非同义、同义或模糊。结果允许单核苷酸、单密码子、滑动窗口、全基因和全基因组/群体分析，其有助于检测源群体中的阳性和纯化自然选择。
New applications of next-generation sequencing technologies use pools of DNA from multiple individuals to estimate population genetic parameters. However, no publicly available tools exist to analyse single-nucleotide polymorphism (SNP) calling results directly for evolutionary parameters important in detecting natural selection, including nucleotide diversity and gene diversity. We have developed SNPGenie to fill this gap. The user submits a FASTA reference sequence(s), a Gene Transfer Format (.GTF) file with CDS information and a SNP report(s) in an increasing selection of formats. The program estimates nucleotide diversity, distance from the reference and gene diversity. Sites are flagged for multiple overlapping reading frames, and are categorized by polymorphism type: nonsynonymous, synonymous, or ambiguous. The results allow single nucleotide, single codon, sliding window, whole gene and whole genome/population analyses that aid in the detection of positive and purifying natural selection in the source population.