Applications of species accumulation curves in large-scale biological data analysis.
Applications of species accumulation curves in large-scale biological data analysis.
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物种积累曲线在大规模生物数据分析中的应用。
DOI：
10.1007/s40484-015-0049-7
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Smith,AndrewD
中科院分区：
文献类型：
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作者：
Deng,Chao;Daley,Timothy;Smith,AndrewD
种群的物种积累曲线或采集者曲线给出了作为取样努力的函数的观察到的物种或不同类别的预期数量。物种累积曲线使研究人员能够评估和比较种群之间的多样性，或评估额外采样的好处。传统的应用集中在生态种群，但新兴的大规模应用，如DNA测序，是数量级更大，提出了新的挑战。我们开发了一种方法来估计积累曲线预测DNA测序库的复杂性。该方法使用有理函数逼近Good和Toulmin的经典非参数经验贝叶斯估计[Biometrika，1956，43，45-63]。在这里，我们展示了同样的方法如何在涉及生物数据集的其他大规模应用中非常有效。这些包括估计微生物物种丰富度，免疫库大小，和基因组组装应用的k聚体多样性。我们展示了如何修改该方法，以解决人口包含一个有效的无限数量的物种，饱和实际上无法达到。我们还介绍了一套灵活的工具，作为一个R包，使这些方法广泛访问。
The species accumulation curve, or collector’s curve, of a population gives the expected number of observed species or distinct classes as a function of sampling effort. Species accumulation curves allow researchers to assess and compare diversity across populations or to evaluate the benefits of additional sampling. Traditional applications have focused on ecological populations but emerging large-scale applications, for example in DNA sequencing, are orders of magnitude larger and present new challenges.We developed a method to estimate accumulation curves for predicting the complexity of DNA sequencing libraries. This method uses rational function approximations to a classical nonparametric empirical Bayes estimator due to Good and Toulmin [Biometrika, 1956, 43, 45–63]. Here we demonstrate how the same approach can be highly effective in other large-scale applications involving biological data sets. These include estimating microbial species richness, immune repertoire size, andk-mer diversity for genome assembly applications. We show how the method can be modified to address populations containing an effectively infinite number of species where saturation cannot practically be attained. We also introduce a flexible suite of tools implemented as an R package that make these methods broadly accessible.