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

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2025-01-29 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf010
Ruben H P Vorderman
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引用次数: 0

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.

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Queer voices in computational biology: the first ISCB LGBTQI+ Symposium. Simplicity within biological complexity. Sequali: efficient and comprehensive quality control of short- and long-read sequencing data. Imputation for Lipidomics and Metabolomics (ImpLiMet): a web-based application for optimization and method selection for missing data imputation. Sphae: an automated toolkit for predicting phage therapy candidates from sequencing data.
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