Computational Pipeline for the Detection of Plant RNA Viruses Using High-Throughput Sequencing-Reference-Cited by-同舟云学术

Computational Pipeline for the Detection of Plant RNA Viruses Using High-Throughput Sequencing

Published:2023-11-22 Issue: Volume: Page:1-20
ISSN:1064-3745
Container-title:Methods in Molecular Biology
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Author:

Donaire Livia,Aranda Miguel A.

Publisher

Springer US

Link

https://link.springer.com/content/pdf/10.1007/978-1-0716-3485-1_1

Reference18 articles.

1. Villamor DEV, Ho T, al Rwahnih M et al (2019) High throughput sequencing for plant virus detection and discovery. Phytopathology 109:716–725. https://doi.org/10.1094/PHYTO-07-18-0257-RVW

2. Kutnjak D, Tamisier L, Adams I et al (2021) A primer on the analysis of high-throughput sequencing data for detection of plant viruses. Microorganisms 9:841. https://doi.org/10.3390/microorganisms9040841

3. Andrews S (2010) FastQC: A quality control tool for high throughput sequence data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Accessed 23 Feb 2023

4. Blawid R, Silva JMF, Nagata T (2017) Discovering and sequencing new plant viral genomes by next-generation sequencing: description of a practical pipeline. Ann Appl Biol 170:301–314. https://doi.org/10.1111/aab.12345

5. Altschup SF, Gish W, Miller W et al (1990) Basic local alignment search tool. J Mol Biol 215:403–410. https://doi.org/10.1016/S0022-2836(05)80360-2

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