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Giraffe: A tool for comprehensive processing and visualization of multiple long-read sequencing data
Xudong Liu1, Yanwen Shao1, Zhihao Guo1
1Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.
Abstract:
Third-generation sequencing techniques have become increasingly popular due to their capacity to produce long, high-quality reads. Effective comparative analysis across various samples and sequencing platforms is essential for understanding biological mechanisms and establishing benchmark baselines. However, existing tools for long-read sequencing predominantly focus on quality control (QC) and processing for individual samples, complicating the comparison of multiple datasets. The lack of comprehensive tools for data comparison and visualization presents challenges for researchers with limited bioinformatics experience. To address this gap, we present Giraffe (https://github.com/lrslab/Giraffe_View), a Python3-based command-line tool designed for comparative analysis and visualization across diverse samples and platforms. Giraffe facilitates the assessment of read quality, sequencing bias, and genomic regional methylation proportions for both DNA and direct RNA sequencing reads. Its effectiveness has been demonstrated in various scenarios, including comparisons of sequencing methods (whole genome amplification vs. shotgun), sequencing platforms (Oxford Nanopore Technology, ONT vs. Pacific Biosciences, PacBio), tissues (kidney marrow with and without blood), and biological replicates (kidney marrows).
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