系统发育树
计算机科学
德布鲁因图
基因组
源代码
DNA测序
计算生物学
生物
数据挖掘
图形
理论计算机科学
基因
遗传学
操作系统
作者
Pulin Xie,Yongling Guo,Wenbin Zhou,Zhen Zhang,Yan Yu
出处
期刊:Authorea - Authorea
日期:2023-04-17
被引量:3
标识
DOI:10.22541/au.168172406.69677221/v1
摘要
The advancement of Next-generation Sequencing (NGS) technologies has led to a revolution in the field of evolutionary biology. With the increasing number of available genomes and transcriptomes, researchers can mine various types of molecular markers that are vital for phylogenetic, evolutionary, and ecological studies. Numerous tools have been developed to extract these molecular markers from NGS data. However, due to a limited number of well-annotated reference genomes for non-model organisms, it is still challenging to obtain these markers accurately and efficiently. Here, we present GeneMiner, an improved and expanded version of our previous tool, Easy353. GeneMiner involves the reference-guided de Bruijn Graph assembly with seed self-discovery and greedy extension. Additionally, it includes a verification step using a parameter-bootstrap method to reduce the negative impact on assembly caused by the relatively distant reference. Our results using both experimental and simulation data showed GeneMiner can accurately acquire phylogenetic molecular markers for plants using transcriptomic, genomic, and other NGS data. GeneMiner is designed to be user-friendly, fast, and memory-efficient, and is compatible with Linux, Windows, and macOS. All source codes are publicly available on GitHub for easy accessibility and transparency (https://github.com/happywithxpl/GeneMiner).
科研通智能强力驱动
Strongly Powered by AbleSci AI