<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wang, Kaile</style></author><author><style face="normal" font="default" size="100%">Lai, Shujuan</style></author><author><style face="normal" font="default" size="100%">Yang, Xiaoxu</style></author><author><style face="normal" font="default" size="100%">Zhu, Tianqi</style></author><author><style face="normal" font="default" size="100%">Xuemei Lu</style></author><author><style face="normal" font="default" size="100%">Chung-I Wu</style></author><author><style face="normal" font="default" size="100%">Ruan, Jue</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Ultrasensitive and high-efficiency screen of de novo low-frequency mutations by o2n-seq</style></title><secondary-title><style face="normal" font="default" size="100%">Nature communications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.nature.com/articles/ncomms15335</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Nature Publishing Group</style></publisher><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">15335</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Detection of &lt;em&gt;de novo&lt;/em&gt;, low-frequency mutations is essential for characterizing cancer genomes and heterogeneous cell populations. However, the screening capacity of current ultrasensitive NGS methods is inadequate owing to either low-efficiency read utilization or severe amplification bias. Here, we present o2n-seq, an ultrasensitive and high-efficiency NGS library preparation method for discovering &lt;em&gt;de novo&lt;/em&gt;, low-frequency mutations. O2n-seq reduces the error rate of NGS to 10&lt;sup&gt;−5&lt;/sup&gt;–10&lt;sup&gt;−8&lt;/sup&gt;. The efficiency of its data usage is about 10–30 times higher than that of barcode-based strategies. For detecting mutations with allele frequency (AF) 1% in 4.6 Mb-sized genome, the sensitivity and specificity of o2n-seq reach to 99% and 98.64%, respectively. For mutations with AF around 0.07% in &lt;em&gt;phix174&lt;/em&gt;, o2n-seq detects all the mutations with 100% specificity. Moreover, we successfully apply o2n-seq to screen &lt;em&gt;de novo&lt;/em&gt;, low-frequency mutations in human tumours. O2n-seq will aid to characterize the landscape of somatic mutations in research and clinical settings.&lt;/p&gt;</style></abstract></record></records></xml>