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GeneMiner: a tool for extracting phylogenetic markers from next-generation sequencing data
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  • Pulin Xie,
  • Yongling Guo,
  • Yue Teng,
  • Wenbin Zhou,
  • Yan Yu
Pulin Xie
Sichuan University
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Yongling Guo
Sichuan University
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Yue Teng
Beijing Institute of Microbiology and Epidemiology
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Wenbin Zhou
The University of North Carolina at Chapel Hill
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Yan Yu
Sichuan University

Corresponding Author:[email protected]

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Abstract

The advancement of next-generation sequencing (NGS) technologies has been revolutionary for the field of evolutionary biology. This technology has led to an abundance of available genomes and transcriptomes for researchers to mine. Specifically, researchers can mine for 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 an insufficient number of well-annotated reference genomes for non-model organisms, it remains challenging to obtain these markers accurately and efficiently. Here, we present GeneMiner, an improved and expanded version of our previous tool, Easy353. GeneMiner combines 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 pitfalls associated with using a relatively distant reference. Our results using both experimental and simulation data showed GeneMiner can accurately acquires phylogenetic molecular markers for plants using transcriptomic, genomic, and other NGS data. GeneMiner is designed to be user-friendly, fast, and memory efficient. Further, it is compatible with Linux, Windows, and macOS. All source codes are publicly available on GitHub for easy accessibility and transparency (https://github.com/yyscu/GeneMiner).
27 Oct 2023Submitted to Molecular Ecology Resources
31 Oct 2023Review(s) Completed, Editorial Evaluation Pending
31 Oct 2023Submission Checks Completed
31 Oct 2023Assigned to Editor
31 Oct 2023Reviewer(s) Assigned