RabbitTrim: An Efficient and Versatile Trimmer on Multi-Core Platforms

Abstract

Trimming is an essential step in sequencing data processing. However, many existing trimming tools, such as Trimmomatic and Ktrim, are limited by suboptimal implementations and fail to fully leverage the computational power of modern multi-core platforms. To address this, we introduce RabbitTrim, a highly optimized and versatile trimming tool that fully supports the functionalities of Trimmomatic and Ktrim. RabbitTrim's performance is enhanced through efficient I/O strategies, parallel (de)compression engines, block-based memory pools, bitwise operations, and vectorization techniques. Compared to Trimmomatic, RabbitTrim (in trimmomatic mode) achieves speedups ranging from 1.8x to 6.0x for plain FASTQ files and 3.7x to 14.0x for gzip-compressed FASTQ files on a 48-core Intel server. Similarly, compared to Ktrim, RabbitTrim (in ktrim mode) achieves speedups ranging from 1.5x to 2.5x for plain FASTQ files and 2.7x to 5.6x for gzip-compressed FASTQ files on the same server. Moreover, RabbitTrim is able to process 101 GB gzip-compressed sequencing data in only 5 minutes while Trimmomatic requires at least 21 minutes. The source code is available at https://github.com/RabbitBio/RabbitTrim.