Evaluation of genomic island predictors using a comparative genomics approach.
Evaluation of genomic island predictors using a comparative genomics approach.
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DOI：
10.1186/1471-2105-9-329
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发表时间：
2008-08-05
影响因子：
3
通讯作者：
Brinkman FS
中科院分区：
文献类型：
--
作者：
Langille MG;Hsiao WW;Brinkman FS
基因组岛（GI）是原核生物基因组中可能水平起源的基因簇。地理标志与医学或环境利益的微生物适应性不成比例地相关。最近，已经开发了多种用于自动检测GI的程序，其利用序列组成特征，例如G+C比和二核苷酸偏倚。为了稳健地评估这些方法的准确性，我们建议使用独立于基于序列组成的分析方法的标准来构建GI数据集。我们开发了一种比较基因组学方法（IslandPick），可以识别非常可能的岛屿和非岛屿地区。该方法涉及1）使用挑选适当基因组以识别GI的距离函数，灵活地自动选择每个查询基因组的比较基因组，2）与所选择的基因组（阳性数据集）相比，识别查询基因组特有的区域，以及3）识别在所有基因组中保守的区域（阴性数据集）。使用我们构建的数据集，我们研究了几种基于序列组成的GI预测工具的准确性。我们的结果表明，AlienHunter具有最高的召回率，但测量精度最低，而SIGI-HMM是最精确的方法。SIGI-HMM和IslandPath/DIMOB具有可比的整体最高准确度。我们的比较基因组学方法，IslandPick，是最准确的，与地理信息系统的策划列表相比，这表明我们已经构建了合适的数据集。这代表了第一次评估，使用不同的，独立的数据集，而不是人工构建的，几个序列组成为基础的GI预测的准确性。与此相关的分析和建议，最佳岛屿预测的警告进行了讨论。
Genomic islands (GIs) are clusters of genes in prokaryotic genomes of probable horizontal origin. GIs are disproportionately associated with microbial adaptations of medical or environmental interest. Recently, multiple programs for automated detection of GIs have been developed that utilize sequence composition characteristics, such as G+C ratio and dinucleotide bias. To robustly evaluate the accuracy of such methods, we propose that a dataset of GIs be constructed using criteria that are independent of sequence composition-based analysis approaches. We developed a comparative genomics approach (IslandPick) that identifies both very probable islands and non-island regions. The approach involves 1) flexible, automated selection of comparative genomes for each query genome, using a distance function that picks appropriate genomes for identification of GIs, 2) identification of regions unique to the query genome, compared with the chosen genomes (positive dataset) and 3) identification of regions conserved across all genomes (negative dataset). Using our constructed datasets, we investigated the accuracy of several sequence composition-based GI prediction tools. Our results indicate that AlienHunter has the highest recall, but the lowest measured precision, while SIGI-HMM is the most precise method. SIGI-HMM and IslandPath/DIMOB have comparable overall highest accuracy. Our comparative genomics approach, IslandPick, was the most accurate, compared with a curated list of GIs, indicating that we have constructed suitable datasets. This represents the first evaluation, using diverse and, independent datasets that were not artificially constructed, of the accuracy of several sequence composition-based GI predictors. The caveats associated with this analysis and proposals for optimal island prediction are discussed.
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影响因子：
3.9
作者：
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通讯作者：
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通讯作者：
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DOI：
10.1073/pnas.152298499
发表时间：
2002-07-23
影响因子：
11.1
作者：
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通讯作者：
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