The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
fastp: an ultra-fast all-in-one FASTQ preprocessor
Open accessPublished version of a preprint
Abstract
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 pruning and many other operations with a single scan of the 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.
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“generating ~117.3 Gb of high-quality 150 bp paired-end reads”
From A complete telomere-to-telomere chromosome-level genome assembly of X-ray tetra (Pristella maxillaris) (2025) · cites this paper as [18]
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Cites
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Metadata
- Authors
- Chen, S., Zhou, Y., Chen, Y., & Gu, J.
- Affiliations
- Chinese Academy of Sciences (CN)
- Department of Bioinformatics, HaploX Biotechnology, Shenzhen, China
- Corresponding author
- Chen, Shifu
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-09-01
- Volume
- 34
- Issue
- 17
- Pages
- i884-i890
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC6129281
- OpenAlex
- W2951912016
- Cited by
- 29,721
- References
- 6
- Citations by year
- 2026: 6556 · 2025: 6937 · 2024: 6063 · 2023: 4192 · 2022: 3147 · 2021: 1820 · 2020: 787 · 2019: 187 · 2018: 9
- FWCI
- 258.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Special Funds for Future Industries of Shenzhen (JSGG20160229123927512)
- National Science Foundation of China (61472411)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- quality control, adapter trimming, quality filtering, multithreading, C++, high-throughput sequencing data, fastp
- MeSH terms
- Humans, Programming Languages, Quality Control
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