Comparison of Sequencing Utility Programs

TLDR

High‑throughput sequencing generates terabytes of data daily, requiring preprocessing steps such as adapter trimming and paired‑end joining before downstream analyses. The study aims to develop two tools to perform adapter trimming and paired‑end joining for high‑throughput sequencing data. The tools, fastq‑mcf and fastq‑join, implement efficient algorithms for adapter trimming and paired‑end joining. Benchmarking showed that fastq‑mcf and fastq‑join outperform comparable open‑source utilities in both resource efficiency and effectiveness.

Abstract

High throughput sequencing (HTS) has resulted in extreme growth rates of sequencing data. At our lab, we generate terabytes of data every day. It is usually seen as required for data output to be “cleaned” and processed in various ways prior to use for common tasks such as variant calling, expression quantification and assembly. Two common tasks associated with HTS are adapter trimming and paired-end joining . I have developed two tools at Expression Analysis, Inc. to address these common tasks. The names of these programs are fastq-mcf and fastq-join . I compared the performance of these tools to similar open-source utilities, both in terms of resource efficiency, and effectiveness.