首页> 外文期刊>Bioinformatics >Gaussian process test for high-throughput sequencing time series: application to experimental evolution
【24h】

Gaussian process test for high-throughput sequencing time series: application to experimental evolution

机译:高通量测序时间序列的高斯过程测试:在实验进化中的应用

获取原文
获取原文并翻译 | 示例
       

摘要

Motivation: Recent advances in high-throughput sequencing (HTS) have made it possible to monitor genomes in great detail. New experiments not only use HTS to measure genomic features at one time point but also monitor them changing over time with the aim of identifying significant changes in their abundance. In population genetics, for example, allele frequencies are monitored over time to detect significant frequency changes that indicate selection pressures. Previous attempts at analyzing data from HTS experiments have been limited as they could not simultaneously include data at intermediate time points, replicate experiments and sources of uncertainty specific to HTS such as sequencing depth.
机译:动机:高通量测序(HTS)的最新进展已使对基因组进行详细监测成为可能。新实验不仅使用HTS在某个时间点测量基因组特征,而且还监视它们随时间的变化,目的是确定其丰度的显着变化。例如,在群体遗传学中,随时间监视等位基因频率以检测指示选择压力的显着频率变化。先前对来自HTS实验的数据进行分析的尝试受到了限制,因为它们无法同时包括中间时间点的数据,重复实验以及特定于HTS的不确定性来源,例如测序深度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号