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Relational database index choices for genome annotation data

机译:基因组注释数据的关系数据库索引选择

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Latest genomics techniques such as ChIP-chip, ChIP-seq, and RNA-seq have induced an exponential growth in the volume of genome annotations. The effective mining of these data is an indispensible step in systems biology. In this work we consider conventional B-tree, R-tree and no index options for annotation data in MySQL, Oracle, and PostgreSQL databases. We validate theoretical considerations of applicability of different indexes by computational experiments with gene, repeat masker, expressed sequence tag, and single nucleotide polymorphism annotations of Homo sapiens chromosome 22. The running times for distance and overlap queries suggest that, with the exception of PostgreSQL B-tree for overlap queries, R-trees are superior to B-trees for indexing annotations, and thus may be a good choice for genome annotation databases.
机译:诸如芯片芯片,芯片SEQ和RNA-SEQ等最新的基因组学技术诱导了基因组注释体积的指数增长。这些数据的有效采矿是系统生物学中不可或缺的步骤。在这项工作中,我们考虑传统的B树,R树,没有索引选项,用于MySQL,Oracle和PostgreSQL数据库中的注释数据。通过基因,重复掩蔽剂,表达序列标签和单核苷酸染色体22的单核苷酸多态性注释,验证了不同指标的适用性的理论考虑。距离和重叠查询的运行时间表明,除了PostgreSQL B之外-Tree用于重叠查询,R树优于B树,用于索引注释,因此可能是基因组注释数据库的良好选择。

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