Suppr超能文献

一种用于个体单倍型分型的更好的区段划分与连接策略。

A better block partition and ligation strategy for individual haplotyping.

作者信息

Zhao Yuzhong, Xu Yun, Wang Zhihao, Zhang Hong, Chen Guoliang

机构信息

Department of Computer Science, University of Science and Technology of China and Anhui Province-MOST Co-Key Laboratory of High Performance Computing and Its Application, Hefei, Anhui 230027, P.R. China.

出版信息

Bioinformatics. 2008 Dec 1;24(23):2720-5. doi: 10.1093/bioinformatics/btn519. Epub 2008 Oct 9.

Abstract

MOTIVATION

Haplotype played an important role in the association studies of disease gene and drug responsivity over the past years, but the low throughput of expensive biological experiments largely limited its application. Alternatively, some efficient statistical methods were developed to deduce haplotypes from genotypes directly. Because these algorithms usually needed to estimate the frequencies of numerous possible haplotypes, the partition and ligation strategy was widely adopted to reduce the time complexity. The haplotypes were usually partitioned uniformly in the past, but recent studies showed that the haplotypes had their own block structure, which may be not uniform. More reasonable block partition and ligation strategy according to the haplotype structure may further improve the accuracy of individual haplotyping.

RESULTS

In this article, we presented a simple algorithm for block partition and ligation, which provided better accuracy for individual haplotyping. The block partition and ligation could be completed within O(m(2) logm+m(2n)) time complexity, where m represented the length of genotypes and n represented the number of individuals. We tested the performance of our algorithm on both real and simulated dataset. The result showed that our algorithm yielded better accuracy with short running time.

AVAILABILITY

The software is publicly available at http://mail.ustc.edu.cn/~zyzh.

摘要

动机

在过去几年中,单倍型在疾病基因和药物反应性的关联研究中发挥了重要作用,但昂贵的生物学实验的低通量在很大程度上限制了其应用。另外,人们开发了一些有效的统计方法来直接从基因型推断单倍型。由于这些算法通常需要估计众多可能单倍型的频率,因此广泛采用划分和连接策略来降低时间复杂度。过去,单倍型通常被均匀划分,但最近的研究表明,单倍型具有自身的块结构,可能并非均匀分布。根据单倍型结构采用更合理的块划分和连接策略可能会进一步提高个体单倍型分型的准确性。

结果

在本文中,我们提出了一种用于块划分和连接的简单算法,该算法为个体单倍型分型提供了更高的准确性。块划分和连接可以在O(m(2) logm + m(2n))时间复杂度内完成,其中m表示基因型的长度,n表示个体的数量。我们在真实数据集和模拟数据集上测试了我们算法的性能。结果表明,我们的算法在运行时间较短的情况下产生了更好的准确性。

可用性

该软件可在http://mail.ustc.edu.cn/~zyzh上公开获取。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验