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高通量数据覆盖度的统计建模

Statistical modeling of coverage in high-throughput data.

作者信息

Golan David, Rosset Saharon

机构信息

School of Mathematical Sciences, Tel Aviv University, Tel Aviv, Israel.

出版信息

Methods Mol Biol. 2013;1038:61-79. doi: 10.1007/978-1-62703-514-9_4.

Abstract

In high-throughput sequencing experiments, the number of reads mapping to a genomic region, also known as the "coverage" or "coverage depth," is often used as a proxy for the abundance of the underlying genomic region in the sample. The abundance, in turn, can be used for many purposes including calling SNPs, estimating the allele frequency in a pool of individuals, identifying copy number variations, and identifying differentially expressed shRNAs in shRNA-seq experiments.In this chapter we describe the fundamentals of statistical modeling of coverage depth and discuss the problems of estimation and inference in the relevant experimental scenarios.

摘要

在高通量测序实验中,映射到基因组区域的 reads 数量,也称为“覆盖度”或“覆盖深度”,通常被用作样本中潜在基因组区域丰度的替代指标。反过来,该丰度可用于多种目的,包括 SNP 检测、估计个体池中等位基因频率、识别拷贝数变异以及在 shRNA-seq 实验中识别差异表达的 shRNA。在本章中,我们描述了覆盖深度统计建模的基本原理,并讨论了相关实验场景中的估计和推断问题。

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