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DNAp: A Pipeline for DNA-seq Data Analysis
Next-generation sequencing is empowering genetic disease research. However, it also brings significant challenges for efficient and effective sequencing data analysis. We built a pipeline, called DNAp, for analyzing whole exome sequencing (WES) and whole genome sequencing (WGS) data, to detect mutat...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931599/ https://www.ncbi.nlm.nih.gov/pubmed/29717215 http://dx.doi.org/10.1038/s41598-018-25022-6 |
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author | Causey, Jason L. Ashby, Cody Walker, Karl Wang, Zhiping Paul Yang, Mary Guan, Yuanfang Moore, Jason H. Huang, Xiuzhen |
author_facet | Causey, Jason L. Ashby, Cody Walker, Karl Wang, Zhiping Paul Yang, Mary Guan, Yuanfang Moore, Jason H. Huang, Xiuzhen |
author_sort | Causey, Jason L. |
collection | PubMed |
description | Next-generation sequencing is empowering genetic disease research. However, it also brings significant challenges for efficient and effective sequencing data analysis. We built a pipeline, called DNAp, for analyzing whole exome sequencing (WES) and whole genome sequencing (WGS) data, to detect mutations from disease samples. The pipeline is containerized, convenient to use and can run under any system, since it is a fully automatic process in Docker container form. It is also open, and can be easily customized with user intervention points, such as for updating reference files and different software or versions. The pipeline has been tested with both human and mouse sequencing datasets, and it has generated mutations results, comparable to published results from these datasets, and reproducible across heterogeneous hardware platforms. The pipeline DNAp, funded by the US Food and Drug Administration (FDA), was developed for analyzing DNA sequencing data of FDA. Here we make DNAp an open source, with the software and documentation available to the public at http://bioinformatics.astate.edu/dna-pipeline/. |
format | Online Article Text |
id | pubmed-5931599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59315992018-08-29 DNAp: A Pipeline for DNA-seq Data Analysis Causey, Jason L. Ashby, Cody Walker, Karl Wang, Zhiping Paul Yang, Mary Guan, Yuanfang Moore, Jason H. Huang, Xiuzhen Sci Rep Article Next-generation sequencing is empowering genetic disease research. However, it also brings significant challenges for efficient and effective sequencing data analysis. We built a pipeline, called DNAp, for analyzing whole exome sequencing (WES) and whole genome sequencing (WGS) data, to detect mutations from disease samples. The pipeline is containerized, convenient to use and can run under any system, since it is a fully automatic process in Docker container form. It is also open, and can be easily customized with user intervention points, such as for updating reference files and different software or versions. The pipeline has been tested with both human and mouse sequencing datasets, and it has generated mutations results, comparable to published results from these datasets, and reproducible across heterogeneous hardware platforms. The pipeline DNAp, funded by the US Food and Drug Administration (FDA), was developed for analyzing DNA sequencing data of FDA. Here we make DNAp an open source, with the software and documentation available to the public at http://bioinformatics.astate.edu/dna-pipeline/. Nature Publishing Group UK 2018-05-01 /pmc/articles/PMC5931599/ /pubmed/29717215 http://dx.doi.org/10.1038/s41598-018-25022-6 Text en © The Author(s) 2018 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/. |
spellingShingle | Article Causey, Jason L. Ashby, Cody Walker, Karl Wang, Zhiping Paul Yang, Mary Guan, Yuanfang Moore, Jason H. Huang, Xiuzhen DNAp: A Pipeline for DNA-seq Data Analysis |
title | DNAp: A Pipeline for DNA-seq Data Analysis |
title_full | DNAp: A Pipeline for DNA-seq Data Analysis |
title_fullStr | DNAp: A Pipeline for DNA-seq Data Analysis |
title_full_unstemmed | DNAp: A Pipeline for DNA-seq Data Analysis |
title_short | DNAp: A Pipeline for DNA-seq Data Analysis |
title_sort | dnap: a pipeline for dna-seq data analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931599/ https://www.ncbi.nlm.nih.gov/pubmed/29717215 http://dx.doi.org/10.1038/s41598-018-25022-6 |
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