Work

Sequali: efficient and comprehensive quality control of short- and long-read sequencing data

Year: 2024

Type: article

Abstract: Motivation: Quality control of sequencing data is the first step in many sequencing workflows. Short- and long-read sequencing technologies have many commonalities with regard to quality control. Several quality control programs exist; however, none possess a feature set that is adequate for both technologies. Quality control programs aimed at Oxford Nanopore Technologies sequencing lack vital features, such as adapter searching, overrepresented sequence analysis, and duplication analysis. Results: Sequali was developed to provide sequencing quality control for both short- and long-read sequencing technologies. It features adapter search, overrepresented sequence analysis, and duplication analysis and supports FASTQ and uBAM inputs. It is significantly faster than comparable sequencing quality control programs for both short- and long-read sequencing technologies. Availability and Implementation: Sequali is an open-source Python application using C extensions and is freely available under the AGPL-3.0 license at https://github.com/rhpvorderman/sequali. The source code for each release is archived at zenodo: https://zenodo.org/doi/10.5281/zenodo.10822485.

Source: Bioinformatics Advances

DOI: 10.1093/bioadv/vbaf010

Author: Ruben H P Vorderman

Institution: Leiden University Medical Center

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,917

Funders: Oxford Nanopore Technologies, Universiteit Leiden, Santen, Leids Universitair Medisch Centrum