...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The American Journal of Tropical Medicine and Hygiene >Nonparametric Binary Classification to Distinguish Closely Related versus Unrelated Plasmodium falciparum Parasites
【24h】

Nonparametric Binary Classification to Distinguish Closely Related versus Unrelated Plasmodium falciparum Parasites

机译：非参数二进制分类以区分密切相关的与不相关的疟原虫寄生虫

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Assessing genetic relatedness of Plasmodium falciparum genotypes is a key component of antimalarial efficacy trials. Previous methods have focused on determining a priori definitions of the level of genetic similarity sufficient to classify two infections as sharing the same strain. However, factors such as mixed-strain infections, allelic suppression, imprecise typing methods, and heterozygosity complicate comparisons of apicomplexan genotypes. Here, we introduce a novel method for nonparametric statistical testing of relatedness for P. falciparum parasites. First, the background distribution of genetic distance between unrelated strains is computed. Second, a threshold genetic distance is computed from this empiric distribution of distances to demarcate genetic distances that are unlikely to have arisen by chance. Third, the genetic distance between paired samples is computed, and paired samples with genetic distances below the threshold are classified as related. The method is designed to work with any arbitrary genetic distance definition. We validated this procedure using two independent approaches to calculating genetic distance. We assessed the concordance of the novel nonparametric classification with a gold-standard Bayesian approach for 175 pairs of recurrent P. falciparum episodes from previously published malaria efficacy trials with microsatellite data from five studies in Guinea and Angola. The novel nonparametric approach was 98% sensitive and 84-89% specific in correctly identifying related genotypes compared with a gold-standard Bayesian algorithm. The approach provides a unified and systematic method to statistically assess relatedness of P. falciparum parasites using arbitrary genetic distance methodologies.
机译：评估恶性疟原虫基因型的遗传相关性是抗疟疗效试验的关键组成部分。以前的方法侧重于确定遗传相似性水平的先验定义，该水平足以将两种感染归类为共享同一菌株。然而，诸如混合菌株感染、等位基因抑制、不精确的分型方法和杂合性等因素使apicomplexan基因型的比较复杂化。在这里，我们介绍了一种新的非参数统计检验恶性疟原虫相关性的方法。首先，计算无关菌株间遗传距离的背景分布。其次，根据经验分布的距离计算阈值遗传距离，以划分不太可能偶然出现的遗传距离。第三，计算成对样本之间的遗传距离，遗传距离低于阈值的成对样本被归类为相关样本。该方法适用于任意遗传距离定义。我们使用两种独立的方法来计算遗传距离，从而验证了这个过程。我们使用几内亚和安哥拉五项研究的微卫星数据，对先前发表的疟疾疗效试验中175对复发性恶性疟原虫发作的新非参数分类与金标准贝叶斯方法的一致性进行了评估。与金标准贝叶斯算法相比，新的非参数方法在正确识别相关基因型方面具有98%的敏感性和84-89%的特异性。该方法为利用任意遗传距离方法统计评估恶性疟原虫的相关性提供了一种统一而系统的方法。

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