RabbitQC: high-speed scalable quality control for sequencing data
Zekun Yin, Hao Zhang, Meiyang Liu, Wen Zhang, Hong-Lei Song, Haidong Lan, Yanjie Wei, Beifang Niu, Bertil Schmidt, Weiguo Liu
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.