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GEN2VCF: a converter for human genome imputation output format to VCF format
BACKGROUND: For a genome-wide association study in humans, genotype imputation is an essential analysis tool for improving association mapping power. When IMPUTE software is used for imputation analysis, an imputation output (GEN format) should be converted to variant call format (VCF) with imputed...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497724/ https://www.ncbi.nlm.nih.gov/pubmed/32803703 http://dx.doi.org/10.1007/s13258-020-00982-0 |
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author | Shin, Dong Mun Hwang, Mi Yeong Kim, Bong-Jo Ryu, Keun Ho Kim, Young Jin |
author_facet | Shin, Dong Mun Hwang, Mi Yeong Kim, Bong-Jo Ryu, Keun Ho Kim, Young Jin |
author_sort | Shin, Dong Mun |
collection | PubMed |
description | BACKGROUND: For a genome-wide association study in humans, genotype imputation is an essential analysis tool for improving association mapping power. When IMPUTE software is used for imputation analysis, an imputation output (GEN format) should be converted to variant call format (VCF) with imputed genotype dosage for association analysis. However, the conversion requires multiple software packages in a pipeline with a large amount of processing time. OBJECTIVE: We developed GEN2VCF, a fast and convenient GEN format to VCF conversion tool with dosage support. METHODS: The performance of GEN2VCF was compared to BCFtools, QCTOOL, and Oncofunco. The test data set was a 1 Mb GEN-formatted file of 5000 samples. To determine the performance of various sample sizes, tests were performed from 1000 to 5000 samples with a step size of 1000. Runtime and memory usage were used as performance measures. RESULTS: GEN2VCF showed drastically increased performances with respect to runtime and memory usage. Runtime and memory usage of GEN2VCF was at least 1.4- and 7.4-fold lower compared to other methods, respectively. CONCLUSIONS: GEN2VCF provides users with efficient conversion from GEN format to VCF with the best-guessed genotype, genotype posterior probabilities, and genotype dosage, as well as great flexibility in implementation with other software packages in a pipeline. |
format | Online Article Text |
id | pubmed-7497724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-74977242020-09-28 GEN2VCF: a converter for human genome imputation output format to VCF format Shin, Dong Mun Hwang, Mi Yeong Kim, Bong-Jo Ryu, Keun Ho Kim, Young Jin Genes Genomics Research Article BACKGROUND: For a genome-wide association study in humans, genotype imputation is an essential analysis tool for improving association mapping power. When IMPUTE software is used for imputation analysis, an imputation output (GEN format) should be converted to variant call format (VCF) with imputed genotype dosage for association analysis. However, the conversion requires multiple software packages in a pipeline with a large amount of processing time. OBJECTIVE: We developed GEN2VCF, a fast and convenient GEN format to VCF conversion tool with dosage support. METHODS: The performance of GEN2VCF was compared to BCFtools, QCTOOL, and Oncofunco. The test data set was a 1 Mb GEN-formatted file of 5000 samples. To determine the performance of various sample sizes, tests were performed from 1000 to 5000 samples with a step size of 1000. Runtime and memory usage were used as performance measures. RESULTS: GEN2VCF showed drastically increased performances with respect to runtime and memory usage. Runtime and memory usage of GEN2VCF was at least 1.4- and 7.4-fold lower compared to other methods, respectively. CONCLUSIONS: GEN2VCF provides users with efficient conversion from GEN format to VCF with the best-guessed genotype, genotype posterior probabilities, and genotype dosage, as well as great flexibility in implementation with other software packages in a pipeline. Springer Singapore 2020-08-16 2020 /pmc/articles/PMC7497724/ /pubmed/32803703 http://dx.doi.org/10.1007/s13258-020-00982-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Article Shin, Dong Mun Hwang, Mi Yeong Kim, Bong-Jo Ryu, Keun Ho Kim, Young Jin GEN2VCF: a converter for human genome imputation output format to VCF format |
title | GEN2VCF: a converter for human genome imputation output format to VCF format |
title_full | GEN2VCF: a converter for human genome imputation output format to VCF format |
title_fullStr | GEN2VCF: a converter for human genome imputation output format to VCF format |
title_full_unstemmed | GEN2VCF: a converter for human genome imputation output format to VCF format |
title_short | GEN2VCF: a converter for human genome imputation output format to VCF format |
title_sort | gen2vcf: a converter for human genome imputation output format to vcf format |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497724/ https://www.ncbi.nlm.nih.gov/pubmed/32803703 http://dx.doi.org/10.1007/s13258-020-00982-0 |
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