Predicting the molecular complexity of sequencing libraries

被引：225

作者：

Daley, Timothy ^{[1
]}

Smith, Andrew D. ^{[2
]}

机构：

[1] Univ So Calif, Dept Math, Los Angeles, CA 90089 USA

[2] Univ So Calif, Los Angeles, CA 90089 USA

来源：

NATURE METHODS | 2013年 / 10卷 / 04期

基金：

美国国家卫生研究院;

关键词：

NUMBER; SAMPLE;

D O I：

10.1038/nmeth.2375

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Predicting the molecular complexity of a genomic sequencing library is a critical but difficult problem in modern sequencing applications. Methods to determine how deeply to sequence to achieve complete coverage or to predict the benefits of additional sequencing are lacking. We introduce an empirical Bayesian method to accurately characterize the molecular complexity of a DNA sample for almost any sequencing application on the basis of limited preliminary sequencing.

引用

页码：325 / +

页数：5

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