个体水平的SNP多样性和相似性特征
Individual-Level SNP Diversity and Similarity Profiles
摘要：
遗传（基因）多样性（杂合性）的经典概念，如Nei（1973：PNAS）和Nei和Li（1979：PNAS）核苷酸多样性是在种群背景下定义的。虽然变异通常是在群体背景下测量的，但变异的基本载体是个体。因此，测量个体相对于参考基因组的变异（例如SNP）（其目前被忽视）当然是其自身的权利。事实上，类似的做法一直是生态学的一个传统，其中多样性度量的基本框架是个体群落样本。我们建议使用Renyi熵导出的希尔数来定义SNP（单核苷酸多态性）多样性（包括α-，β-和γ-二聚体）和相似性概况。Hill数是由Renyi熵导出的，Shannon熵是其中的一个特例，在量子信息纠缠的度量、经济学中的财富分配、生态多样性等方面有着广泛的应用。新提出的SNP多样性不仅通过提供个体水平的指标来补充现有的遗传多样性〈动〉性<动>概念，而且还为更高水平的比较遗传分析提供了构建模块。概况概念还有助于解决多样性测量中的一个难题：从各种多样性指数中进行选择，因为多样性概况将一些最常用的指数（作为特殊情况）与不同的多样性顺序（沿着基因突变的稀有性-常见性谱）统一起来。最后，可以用稀疏方法估计谱，这可能有助于减轻测序覆盖不足的一些影响。
英文摘要：
Classic concepts of genetic (gene) diversity (heterozygosity) such as Nei (1973: PNAS) and Nei and Li (1979: PNAS) nucleotide diversity were defined within the context of populations. Although variations are often measured in population context, the basic carriers of variation are individuals. Hence, measuring variations such as SNP of individual against a reference genome, which has been ignored currently, is certainly of its own right. Indeed, similar practice has been a tradition in ecology, where the basic framework of diversity measure is individual community sample. We propose to use Renyi-entropy-derived Hill numbers to define SNP (single nucleotide polymorphism) diversity (including alpha-, beta-, and gamma-diversities) and similarity profiles. Hill numbers are derived from Renyi entropy, of which Shannon entropy is a special case and which have found widely applications including measuring the quantum information entanglement, wealth distribution in economics and ecological diversity. The newly proposed SNP diversity not only complements the existing genetic diversity concepts by offering individual-level metrics, but also offers building blocks for comparative genetic analysis at higher levels. The profile concept also helps to resolve a dilemma in measuring diversity: the choice from various diversity indexes, because diversity profile unifies some of the most commonly used indexes (as special cases) with different diversity orders (along the rareness-commonness spectrum of gene mutations). Finally, the profiles can be estimated with rarefaction approach, which may help to relieve some effect of insufficient sequencing coverage.
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。
