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测序深度和覆盖度:基因组分析中的关键考虑因素。

Sequencing depth and coverage: key considerations in genomic analyses.

机构信息

Computational Genomics Analysis and Training Programme, Medical Research Council Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, Le Gros Clark Building, University of Oxford, Parks Road, Oxford OX1 3PT, UK.

出版信息

Nat Rev Genet. 2014 Feb;15(2):121-32. doi: 10.1038/nrg3642.

Abstract

Sequencing technologies have placed a wide range of genomic analyses within the capabilities of many laboratories. However, sequencing costs often set limits to the amount of sequences that can be generated and, consequently, the biological outcomes that can be achieved from an experimental design. In this Review, we discuss the issue of sequencing depth in the design of next-generation sequencing experiments. We review current guidelines and precedents on the issue of coverage, as well as their underlying considerations, for four major study designs, which include de novo genome sequencing, genome resequencing, transcriptome sequencing and genomic location analyses (for example, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and chromosome conformation capture (3C)).

摘要

测序技术使许多实验室都能够进行广泛的基因组分析。然而,测序成本通常限制了可以生成的序列数量,从而限制了从实验设计中可以获得的生物学结果。在这篇综述中,我们讨论了下一代测序实验设计中测序深度的问题。我们回顾了关于覆盖范围的当前指南和先例,以及它们对于四种主要研究设计的基本考虑,这些设计包括从头测序、基因组重测序、转录组测序和基因组定位分析(例如,染色质免疫沉淀 followed by sequencing(ChIP-seq)和染色体构象捕获(3C))。

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