ArticleiMeta2023
Ultrafast one-pass FASTQ data preprocessing, quality control, and deduplication using fastp.
Article in iMeta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,346 papers.
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Who cites it
1,346 citing papers in PubMed.
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1,286 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A large amount of sequencing data is generated and processed every day with the continuous evolution of sequencing technology and the expansion of sequencing applications. One consequence of such sequencing data explosion is the increasing cost and complexity of data processing. The preprocessing of FASTQ data, which means removing adapter contamination, filtering low-quality reads, and correcting wrongly represented bases, is an indispensable but resource intensive part of sequencing data analysis. Therefore, although a lot of software applications have been developed to solve this problem, bioinformatics scientists and engineers are still pursuing faster, simpler, and more energy-efficient software. Several years ago, the author developed fastp, which is an ultrafast all-in-one FASTQ data preprocessor with many modern features. This software has been approved by many bioinformatics users and has been continuously maintained and updated. Since the first publication on fastp, it has been greatly improved, making it even faster and more powerful. For instance, the duplication evaluation module has been improved, and a new deduplication module has been added. This study aimed to introduce the new features of fastp and demonstrate how it was designed and implemented.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.