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首页> 外文期刊>BMC Bioinformatics >MIA: Mutual Information Analyzer, a graphic user interface program that calculates entropy, vertical and horizontal mutual information of molecular sequence sets
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MIA: Mutual Information Analyzer, a graphic user interface program that calculates entropy, vertical and horizontal mutual information of molecular sequence sets

机译:MIA:互信息分析器,一种图形用户界面程序,用于计算分子序列集的熵,垂直和水平互信息

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摘要

Short and long range correlations in biological sequences are central in genomic studies of covariation. These correlations can be studied using mutual information because it measures the amount of information one random variable contains about the other. Here we present MIA (Mutual Information Analyzer) a user friendly graphic interface pipeline that calculates spectra of vertical entropy (VH), vertical mutual information (VMI) and horizontal mutual information (HMI), since currently there is no user friendly integrated platform that in a single package perform all these calculations. MIA also calculates Jensen-Shannon Divergence (JSD) between pair of different species spectra, herein called informational distances. Thus, the resulting distance matrices can be presented by distance histograms and informational dendrograms, giving support to discrimination of closely related species. In order to test MIA we analyzed sequences from Drosophila Adh locus, because the taxonomy and evolutionary patterns of different Drosophila species are well established and the gene Adh is extensively studied. The search retrieved 959 sequences of 291 species. From the total, 450 sequences of 17 species were selected. With this dataset MIA performed all tasks in less than three hours: gathering, storing and aligning fasta files; calculating VH, VMI and HMI spectra; and calculating JSD between pair of different species spectra. For each task MIA saved tables and graphics in the local disk, easily accessible for future analysis. Our tests revealed that the “informational model free” spectra may represent species signatures. Since JSD applied to Horizontal Mutual Information spectra resulted in statistically significant distances between species, we could calculate respective hierarchical clusters, herein called Informational Dendrograms (ID). When compared to phylogenetic trees all Informational Dendrograms presented similar taxonomy and species clusterization.
机译:生物序列中的短期和长期相关性是协变基因组研究的核心。可以使用互信息来研究这些相关性,因为它可以测量一个随机变量包含的有关另一个变量的信息量。在这里,我们介绍了MIA(互信息分析器),它是一种用户友好的图形界面管道,可计算垂直熵(VH),垂直互信息(VMI)和水平互信息(HMI)的频谱,因为目前尚无用户友好的集成平台。单个程序包即可执行所有这些计算。 MIA还计算一对不同物种光谱之间的詹森-香农发散度(JSD),在此称为信息距离。因此,可以通过距离直方图和信息树状图来表示所得的距离矩阵,从而为区分密切相关的物种提供了支持。为了测试MIA,我们分析了果蝇Adh基因座的序列,因为不同果蝇物种的分类学和进化模式已经很好地建立,并且对Adh基因进行了广泛的研究。搜索检索到291个物种的959个序列。从总数中,选择了17种的450个序列。 MIA使用此数据集在不到三个小时的时间内完成了所有任务:收集,存储和对齐fasta文件;计算VH,VMI和HMI频谱;并计算一对不同物种光谱之间的JSD。对于每项任务,MIA都将表和图形保存在本地磁盘中,便于将来进行分析。我们的测试表明,“无信息模型”光谱可能表示物种特征。由于JSD应用于水平互信息谱导致物种之间的统计距离显着,因此我们可以计算相应的层次聚类,这里称为信息树状图(ID)。与系统树相比,所有信息树形图都具有相似的分类学和物种聚类。

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