College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
College of Science, Hangzhou Dianzi University, Hangzhou, China.
BMC Bioinformatics. 2020 Apr 29;21(1):159. doi: 10.1186/s12859-020-3501-2.
Genomic islands are associated with microbial adaptations, carrying genomic signatures different from the host. Some methods perform an overall test to identify genomic islands based on their local features. However, regions of different scales will display different genomic features.
We proposed here a novel method "2SigFinder ", the first combined use of small-scale and large-scale statistical testing for genomic island detection. The proposed method was tested by genomic island boundary detection and identification of genomic islands or functional features of real biological data. We also compared the proposed method with the comparative genomics and composition-based approaches. The results indicate that the proposed 2SigFinder is more efficient in identifying genomic islands.
From real biological data, 2SigFinder identified genomic islands from a single genome and reported robust results across different experiments, without annotated information of genomes or prior knowledge from other datasets. 2SigHunter identified 25 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats from 27 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats, and detected 101 Phage and 28 HEG out of 130 Phage and 36 HEGs in S. enterica Typhi CT18, which shows that it is more efficient in detecting functional features associated with GIs.
基因组岛与微生物适应有关，携带与宿主不同的基因组特征。一些方法基于其局部特征进行整体测试来识别基因组岛。然而，不同尺度的区域将显示不同的基因组特征。
我们在这里提出了一种新的方法“2SigFinder”，这是首次将小尺度和大尺度统计测试结合起来用于基因组岛检测。所提出的方法通过基因组岛边界检测和真实生物数据中基因组岛或功能特征的识别进行了测试。我们还将该方法与比较基因组学和基于组成的方法进行了比较。结果表明，所提出的 2SigFinder 在识别基因组岛方面更有效。
从真实的生物数据中，2SigFinder 从单个基因组中识别出基因组岛，并在不同的实验中报告了稳健的结果，而无需基因组的注释信息或来自其他数据集的先验知识。2SigHunter 从 27 种致病性、1 种 tRNA、2 种毒力和 2 种重复中鉴定出 25 种致病性、1 种 tRNA、2 种毒力和 2 种重复，并从伤寒沙门氏菌 CT18 中的 130 种噬菌体和 36 种 HEG 中检测到 101 种噬菌体和 28 种 HEG，这表明它在检测与 GIs 相关的功能特征方面更有效。
