Suppr超能文献

NCOurd:NCO 事件和基因转换轨迹的长度分布建模。

NCOurd: modelling length distributions of NCO events and gene conversion tracts.

机构信息

deCODE genetics, Reykjavik 102, Iceland.

School of Technology, Reykjavik University, Reykjavik 102, Iceland.

出版信息

Bioinformatics. 2023 Aug 1;39(8). doi: 10.1093/bioinformatics/btad485.

Abstract

MOTIVATION

Meiotic recombination is the main driving force of human genetic diversity, along with mutations. Recombinations split into crossovers, separating large chromosomal regions originating from different homologous chromosomes, and non-crossovers (NCOs), where a small segment from one chromosome is embedded in a region originating from the homologous chromosome. NCOs are much less studied than mutations and crossovers as NCOs are short and can only be detected at markers heterozygous in the transmitting parent, leaving most of them undetectable.

RESULTS

The detectable NCOs, known as gene conversions, hide information about NCOs, including their number and length, waiting to be unveiled. We introduce NCOurd, software, and algorithm, based on an expectation-maximization algorithm, to estimate the number of NCOs and their length distribution from gene conversion data.

AVAILABILITY AND IMPLEMENTATION

https://github.com/DecodeGenetics/NCOurd.

摘要

动机

减数分裂重组是人类遗传多样性的主要驱动力,与突变一起。重组分为交叉,将来自不同同源染色体的大染色体区域分开,以及非交叉(NCOs),其中一个染色体的一小段嵌入来自同源染色体的区域。NCOs 的研究比突变和交叉少得多,因为 NCOs 很短,只能在传递亲本中杂合的标记处检测到,这使得大多数 NCOs 无法检测到。

结果

可检测的 NCOs,称为基因转换,隐藏了关于 NCOs 的信息,包括它们的数量和长度,等待被揭示。我们引入了 NCOurd,这是一款软件和算法,基于期望最大化算法,用于从基因转换数据中估计 NCOs 的数量及其长度分布。

可用性和实现

https://github.com/DecodeGenetics/NCOurd。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验