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Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools
We produced an extensive collection of deep re-sequencing datasets for the Venter/HuRef genome using the Illumina massively-parallel DNA sequencing platform. The original Venter genome sequence is a very-high quality phased assembly based on Sanger sequencing. Therefore, researchers developing novel...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298255/ https://www.ncbi.nlm.nih.gov/pubmed/30561434 http://dx.doi.org/10.1038/sdata.2018.261 |
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author | Zhou, Bo Arthur, Joseph G. Ho, Steve S. Pattni, Reenal Huang, Yiling Wong, Wing H. Urban, Alexander E. |
author_facet | Zhou, Bo Arthur, Joseph G. Ho, Steve S. Pattni, Reenal Huang, Yiling Wong, Wing H. Urban, Alexander E. |
author_sort | Zhou, Bo |
collection | PubMed |
description | We produced an extensive collection of deep re-sequencing datasets for the Venter/HuRef genome using the Illumina massively-parallel DNA sequencing platform. The original Venter genome sequence is a very-high quality phased assembly based on Sanger sequencing. Therefore, researchers developing novel computational tools for the analysis of human genome sequence variation for the dominant Illumina sequencing technology can test and hone their algorithms by making variant calls from these Venter/HuRef datasets and then immediately confirm the detected variants in the Sanger assembly, freeing them of the need for further experimental validation. This process also applies to implementing and benchmarking existing genome analysis pipelines. We prepared and sequenced 200 bp and 350 bp short-insert whole-genome sequencing libraries (sequenced to 100x and 40x genomic coverages respectively) as well as 2 kb, 5 kb, and 12 kb mate-pair libraries (49x, 122x, and 145x physical coverages respectively). Lastly, we produced a linked-read library (128x physical coverage) from which we also performed haplotype phasing. |
format | Online Article Text |
id | pubmed-6298255 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62982552018-12-19 Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools Zhou, Bo Arthur, Joseph G. Ho, Steve S. Pattni, Reenal Huang, Yiling Wong, Wing H. Urban, Alexander E. Sci Data Data Descriptor We produced an extensive collection of deep re-sequencing datasets for the Venter/HuRef genome using the Illumina massively-parallel DNA sequencing platform. The original Venter genome sequence is a very-high quality phased assembly based on Sanger sequencing. Therefore, researchers developing novel computational tools for the analysis of human genome sequence variation for the dominant Illumina sequencing technology can test and hone their algorithms by making variant calls from these Venter/HuRef datasets and then immediately confirm the detected variants in the Sanger assembly, freeing them of the need for further experimental validation. This process also applies to implementing and benchmarking existing genome analysis pipelines. We prepared and sequenced 200 bp and 350 bp short-insert whole-genome sequencing libraries (sequenced to 100x and 40x genomic coverages respectively) as well as 2 kb, 5 kb, and 12 kb mate-pair libraries (49x, 122x, and 145x physical coverages respectively). Lastly, we produced a linked-read library (128x physical coverage) from which we also performed haplotype phasing. Nature Publishing Group 2018-12-18 /pmc/articles/PMC6298255/ /pubmed/30561434 http://dx.doi.org/10.1038/sdata.2018.261 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Zhou, Bo Arthur, Joseph G. Ho, Steve S. Pattni, Reenal Huang, Yiling Wong, Wing H. Urban, Alexander E. Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools |
title | Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools |
title_full | Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools |
title_fullStr | Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools |
title_full_unstemmed | Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools |
title_short | Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools |
title_sort | extensive and deep sequencing of the venter/huref genome for developing and benchmarking genome analysis tools |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298255/ https://www.ncbi.nlm.nih.gov/pubmed/30561434 http://dx.doi.org/10.1038/sdata.2018.261 |
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