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RabbitQC: high-speed scalable quality control for sequencing data

Zekun Yin^1,2, Hao Zhang¹, Meiyang Liu¹

¹School of Software, Shandong University, Jinan, China.

Bioinformatics (Oxford, England)

|August 14, 2020

Abstract

Motivation:

Modern sequencing technologies continue to revolutionize many areas of biology and medicine. Since the generated datasets are error-prone, downstream applications usually require quality control methods to pre-process FASTQ files. However, existing tools for this task are currently not able to fully exploit the capabilities of computing platforms leading to slow runtimes.

Results:

We present RabbitQC, an extremely fast integrated quality control tool for FASTQ files, which can take full advantage of modern hardware. It includes a variety of operations and supports different sequencing technologies (Illumina, Oxford Nanopore and PacBio). RabbitQC achieves speedups between one and two orders-of-magnitude compared to other state-of-the-art tools.

Availability And Implementation:

C++ sources and binaries are available at https://github.com/ZekunYin/RabbitQC.

Supplementary Information:

Supplementary data are available at Bioinformatics online.

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