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GTQC: Automated Genotyping Array Quality Control and Report
Genotyping array is the most economical approach for conducting large-scale genome-wide genetic association studies. Thorough quality control is key to generating high integrity genotyping data and robust results. Quality control of genotyping array is generally a complicated process, as it requires...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922302/ https://www.ncbi.nlm.nih.gov/pubmed/35300047 http://dx.doi.org/10.7150/jgen.69860 |
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author | Zhao, Shilin Jiang, Limin Yu, Hui Guo, Yan |
author_facet | Zhao, Shilin Jiang, Limin Yu, Hui Guo, Yan |
author_sort | Zhao, Shilin |
collection | PubMed |
description | Genotyping array is the most economical approach for conducting large-scale genome-wide genetic association studies. Thorough quality control is key to generating high integrity genotyping data and robust results. Quality control of genotyping array is generally a complicated process, as it requires intensive manual labor in implementing the established protocols and curating a comprehensive quality report. There is an urgent need to reduce manual intervention via an automated quality control process. Based on previously established protocols and strategies, we developed an R package GTQC (GenoTyping Quality Control) to automate a majority of the quality control steps for general array genotyping data. GTQC covers a comprehensive spectrum of genotype data quality metrics and produces a detailed HTML report comprising tables and figures. Here, we describe the concepts underpinning GTQC and demonstrate its effectiveness using a real genotyping dataset. R package GTQC streamlines a majority of the quality control steps and produces a detailed HTML report on a plethora of quality control metrics, thus enabling a swift and rigorous data quality inspection prior to downstream GWAS and related analyses. By significantly cutting down on the time on genotyping quality control procedures, GTQC ensures maximum utilization of available resources and minimizes waste and inefficient allocation of manual efforts. GTQC tool can be accessed at https://github.com/slzhao/GTQC. |
format | Online Article Text |
id | pubmed-8922302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-89223022022-03-16 GTQC: Automated Genotyping Array Quality Control and Report Zhao, Shilin Jiang, Limin Yu, Hui Guo, Yan J Genomics Research Paper Genotyping array is the most economical approach for conducting large-scale genome-wide genetic association studies. Thorough quality control is key to generating high integrity genotyping data and robust results. Quality control of genotyping array is generally a complicated process, as it requires intensive manual labor in implementing the established protocols and curating a comprehensive quality report. There is an urgent need to reduce manual intervention via an automated quality control process. Based on previously established protocols and strategies, we developed an R package GTQC (GenoTyping Quality Control) to automate a majority of the quality control steps for general array genotyping data. GTQC covers a comprehensive spectrum of genotype data quality metrics and produces a detailed HTML report comprising tables and figures. Here, we describe the concepts underpinning GTQC and demonstrate its effectiveness using a real genotyping dataset. R package GTQC streamlines a majority of the quality control steps and produces a detailed HTML report on a plethora of quality control metrics, thus enabling a swift and rigorous data quality inspection prior to downstream GWAS and related analyses. By significantly cutting down on the time on genotyping quality control procedures, GTQC ensures maximum utilization of available resources and minimizes waste and inefficient allocation of manual efforts. GTQC tool can be accessed at https://github.com/slzhao/GTQC. Ivyspring International Publisher 2022-02-14 /pmc/articles/PMC8922302/ /pubmed/35300047 http://dx.doi.org/10.7150/jgen.69860 Text en © The author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Research Paper Zhao, Shilin Jiang, Limin Yu, Hui Guo, Yan GTQC: Automated Genotyping Array Quality Control and Report |
title | GTQC: Automated Genotyping Array Quality Control and Report |
title_full | GTQC: Automated Genotyping Array Quality Control and Report |
title_fullStr | GTQC: Automated Genotyping Array Quality Control and Report |
title_full_unstemmed | GTQC: Automated Genotyping Array Quality Control and Report |
title_short | GTQC: Automated Genotyping Array Quality Control and Report |
title_sort | gtqc: automated genotyping array quality control and report |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922302/ https://www.ncbi.nlm.nih.gov/pubmed/35300047 http://dx.doi.org/10.7150/jgen.69860 |
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