snpQT: flexible, reproducible, and comprehensive quality control and imputation of genomic data

Christina Vasilopoulou, Benjamin Wingfield, Andrew P Morris, William Duddy

Research output: Contribution to journalArticlepeer-review

77 Downloads (Pure)

Abstract

Quality control of genomic data is an essential but complicated multi-step procedure, often requiring separate installation and expert familiarity with a combination of different bioinformatics tools. Software incompatibilities, and inconsistencies across computing environments, are recurrent challenges, leading to poor reproducibility. Existing semi-automated or automated solutions lack comprehensive quality checks, flexible workflow architecture, and user control. To address these challenges, we have developed snpQT: a scalable, stand-alone software pipeline using nextflow and BioContainers, for comprehensive, reproducible and interactive quality control of human genomic data. snpQT offers some 36 discrete quality filters or correction steps in a complete standardised pipeline, producing graphical reports to demonstrate the state of data before and after each quality control procedure. This includes human genome build conversion, population stratification against data from the 1,000 Genomes Project, automated population outlier removal, and built-in imputation with its own pre- and post- quality controls. Common input formats are used, and a synthetic dataset and comprehensive online tutorial are provided for testing, educational purposes, and demonstration. The snpQT pipeline is designed to run with minimal user input and coding experience; quality control steps are implemented with numerous user-modifiable thresholds, and workflows can be flexibly combined in custom combinations. snpQT is open source and freely available at https://github.com/nebfield/snpQT. A comprehensive online tutorial and installation guide is provided through to GWAS (https://snpqt.readthedocs.io/en/latest/), introducing snpQT using a synthetic demonstration dataset and a real-world Amyotrophic Lateral Sclerosis SNP-array dataset. [Abstract copyright: Copyright: © 2021 Vasilopoulou C et al.]
Original languageEnglish
Article number567
Pages (from-to)1-27
Number of pages27
JournalF1000Research
Volume10
DOIs
Publication statusPublished - 1 Dec 2021

Bibliographical note

Funding Information:
We would like to thank Dr. Priyank Shukla for helpful discussion, Dr. Apostolos Malatras for his assistance, and Peter Timlett for designing the snpQT logo.

Publisher Copyright:
© 2021 Vasilopoulou C et al.

Keywords

  • Population Stratification
  • Quality Control
  • Anaconda
  • GWAS
  • BioContainers
  • Nextflow
  • Imputation
  • SNPs
  • Genomic Variants
  • GWAS pipeline
  • QC
  • Gwas
  • Reproducibility of Results
  • Genomics
  • Humans
  • Gwas Pipeline
  • Biocontainers
  • Qc
  • Quality control
  • Software
  • Genome

Fingerprint

Dive into the research topics of 'snpQT: flexible, reproducible, and comprehensive quality control and imputation of genomic data'. Together they form a unique fingerprint.

Cite this