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基因组图谱统计与生物信息学。

Genome mapping statistics and bioinformatics.

作者信息

Mychaleckyj Josyf C

机构信息

Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.

出版信息

Methods Mol Biol. 2007;404:461-88. doi: 10.1007/978-1-59745-530-5_22.

Abstract

The unprecedented availability of genome sequences, coupled with user-friendly, web-enabled search and analysis tools allows practitioners to locate interesting genome features or sequence tracts with relative ease. Although many public model organism- and genome-mapping resources offer pre-mapped genome browsing, biologists also still need to perform de novo mapping analyses. Correct interpretation of the results in genome annotation databases or the results of one's individual analyses requires at least a conceptual understanding of the statistics and mechanics of genome searches, the expected results from statistical considerations, as well as the algorithms used by different search tools. This chapter introduces the basic statistical results that underlie mapping of nucleotide sequences to genomes and briefly surveys the common programs and algorithms that are used to perform genome mapping, all available via public hosted web sites. Selection of the appropriate sequence search and mapping tool will often demand tradeoffs in sensitivity and specificity relating to the statistics of the search.

摘要

基因组序列前所未有的可得性,再加上用户友好的、基于网络的搜索和分析工具,使得从业者能够相对轻松地找到有趣的基因组特征或序列片段。尽管许多公共的模式生物和基因组图谱资源提供了预映射的基因组浏览功能,但生物学家仍然需要进行从头映射分析。要正确解读基因组注释数据库中的结果或个人分析的结果,至少需要对基因组搜索的统计数据和机制、统计考量的预期结果以及不同搜索工具所使用的算法有概念性的理解。本章介绍了将核苷酸序列映射到基因组的基础统计结果,并简要概述了用于执行基因组映射的常见程序和算法,所有这些都可通过公共托管网站获得。选择合适的序列搜索和映射工具通常需要在与搜索统计相关的灵敏度和特异性之间进行权衡。

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