fastp : an ultra-fast all-in-one FASTQ preprocessor
Shifu Chen, Yanqing Zhou, Yaru Chen, Jia Gu
Shenzhen Institutes of Advanced Technology Mellanox Technologies (Israel)
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming, and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g., Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality cutting, and many other operations with a single scan of the FASTQ data. It also supports unique molecular identifier preprocessing, poly tail trimming, output splitting, and base correction for paired-end data. It can automatically detect adapters for single-end and paired-end FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and Implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp Contact chen@haplox.com
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
化学Mass Spectrometry Techniques and Applications
Protein Structure and Dynamics · Machine Learning in Materials Science
参考文献 13
此处列出前 3 条
引用本文 182
按被引量排序,此处列出前 3 条