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GWASinspector: comprehensive quality control of genome-wide association study results

SUMMARY: Quality control (QC) of genome wide association study (GWAS) result files has become increasingly difficult due to advances in genomic technology. The main challenges include continuous increases in the number of polymorphic genetic variants contained in recent GWASs and reference panels, t...

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Autores principales: Ani, Alireza, van der Most, Peter J, Snieder, Harold, Vaez, Ahmad, Nolte, Ilja M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034536/
https://www.ncbi.nlm.nih.gov/pubmed/33416854
http://dx.doi.org/10.1093/bioinformatics/btaa1084
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author Ani, Alireza
van der Most, Peter J
Snieder, Harold
Vaez, Ahmad
Nolte, Ilja M
author_facet Ani, Alireza
van der Most, Peter J
Snieder, Harold
Vaez, Ahmad
Nolte, Ilja M
author_sort Ani, Alireza
collection PubMed
description SUMMARY: Quality control (QC) of genome wide association study (GWAS) result files has become increasingly difficult due to advances in genomic technology. The main challenges include continuous increases in the number of polymorphic genetic variants contained in recent GWASs and reference panels, the rising number of cohorts participating in a GWAS consortium, and inclusion of new variant types. Here, we present GWASinspector, a flexible R package for comprehensive QC of GWAS results. This package is compatible with recent imputation reference panels, handles insertion/deletion and multi-allelic variants, provides extensive QC reports and efficiently processes big data files. Reference panels covering three human genome builds (NCBI36, GRCh37 and GRCh38) are available. GWASinspector has a user friendly design and allows easy set-up of the QC pipeline through a configuration file. In addition to checking and reporting on individual files, it can be used in preparation of a meta-analysis by testing for systemic differences between studies and generating cleaned, harmonized GWAS files. Comparison with existing GWAS QC tools shows that the main advantages of GWASinspector are its ability to more effectively deal with insertion/deletion and multi-allelic variants and its relatively low memory use. AVAILABILITY AND IMPLEMENTATION: Our package is available at The Comprehensive R Archive Network (CRAN): https://CRAN.R-project.org/package=GWASinspector. Reference datasets and a detailed tutorial can be found at the package website at http://gwasinspector.com/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-80345362021-04-14 GWASinspector: comprehensive quality control of genome-wide association study results Ani, Alireza van der Most, Peter J Snieder, Harold Vaez, Ahmad Nolte, Ilja M Bioinformatics Applications Notes SUMMARY: Quality control (QC) of genome wide association study (GWAS) result files has become increasingly difficult due to advances in genomic technology. The main challenges include continuous increases in the number of polymorphic genetic variants contained in recent GWASs and reference panels, the rising number of cohorts participating in a GWAS consortium, and inclusion of new variant types. Here, we present GWASinspector, a flexible R package for comprehensive QC of GWAS results. This package is compatible with recent imputation reference panels, handles insertion/deletion and multi-allelic variants, provides extensive QC reports and efficiently processes big data files. Reference panels covering three human genome builds (NCBI36, GRCh37 and GRCh38) are available. GWASinspector has a user friendly design and allows easy set-up of the QC pipeline through a configuration file. In addition to checking and reporting on individual files, it can be used in preparation of a meta-analysis by testing for systemic differences between studies and generating cleaned, harmonized GWAS files. Comparison with existing GWAS QC tools shows that the main advantages of GWASinspector are its ability to more effectively deal with insertion/deletion and multi-allelic variants and its relatively low memory use. AVAILABILITY AND IMPLEMENTATION: Our package is available at The Comprehensive R Archive Network (CRAN): https://CRAN.R-project.org/package=GWASinspector. Reference datasets and a detailed tutorial can be found at the package website at http://gwasinspector.com/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-01-08 /pmc/articles/PMC8034536/ /pubmed/33416854 http://dx.doi.org/10.1093/bioinformatics/btaa1084 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Ani, Alireza
van der Most, Peter J
Snieder, Harold
Vaez, Ahmad
Nolte, Ilja M
GWASinspector: comprehensive quality control of genome-wide association study results
title GWASinspector: comprehensive quality control of genome-wide association study results
title_full GWASinspector: comprehensive quality control of genome-wide association study results
title_fullStr GWASinspector: comprehensive quality control of genome-wide association study results
title_full_unstemmed GWASinspector: comprehensive quality control of genome-wide association study results
title_short GWASinspector: comprehensive quality control of genome-wide association study results
title_sort gwasinspector: comprehensive quality control of genome-wide association study results
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034536/
https://www.ncbi.nlm.nih.gov/pubmed/33416854
http://dx.doi.org/10.1093/bioinformatics/btaa1084
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