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SeqMule: automated pipeline for analysis of human exome/genome sequencing data
Next-generation sequencing (NGS) technology has greatly helped us identify disease-contributory variants for Mendelian diseases. However, users are often faced with issues such as software compatibility, complicated configuration, and no access to high-performance computing facility. Discrepancies e...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585643/ https://www.ncbi.nlm.nih.gov/pubmed/26381817 http://dx.doi.org/10.1038/srep14283 |
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author | Guo, Yunfei Ding, Xiaolei Shen, Yufeng Lyon, Gholson J. Wang, Kai |
author_facet | Guo, Yunfei Ding, Xiaolei Shen, Yufeng Lyon, Gholson J. Wang, Kai |
author_sort | Guo, Yunfei |
collection | PubMed |
description | Next-generation sequencing (NGS) technology has greatly helped us identify disease-contributory variants for Mendelian diseases. However, users are often faced with issues such as software compatibility, complicated configuration, and no access to high-performance computing facility. Discrepancies exist among aligners and variant callers. We developed a computational pipeline, SeqMule, to perform automated variant calling from NGS data on human genomes and exomes. SeqMule integrates computational-cluster-free parallelization capability built on top of the variant callers, and facilitates normalization/intersection of variant calls to generate consensus set with high confidence. SeqMule integrates 5 alignment tools, 5 variant calling algorithms and accepts various combinations all by one-line command, therefore allowing highly flexible yet fully automated variant calling. In a modern machine (2 Intel Xeon X5650 CPUs, 48 GB memory), when fast turn-around is needed, SeqMule generates annotated VCF files in a day from a 30X whole-genome sequencing data set; when more accurate calling is needed, SeqMule generates consensus call set that improves over single callers, as measured by both Mendelian error rate and consistency. SeqMule supports Sun Grid Engine for parallel processing, offers turn-key solution for deployment on Amazon Web Services, allows quality check, Mendelian error check, consistency evaluation, HTML-based reports. SeqMule is available at http://seqmule.openbioinformatics.org. |
format | Online Article Text |
id | pubmed-4585643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-45856432015-09-29 SeqMule: automated pipeline for analysis of human exome/genome sequencing data Guo, Yunfei Ding, Xiaolei Shen, Yufeng Lyon, Gholson J. Wang, Kai Sci Rep Article Next-generation sequencing (NGS) technology has greatly helped us identify disease-contributory variants for Mendelian diseases. However, users are often faced with issues such as software compatibility, complicated configuration, and no access to high-performance computing facility. Discrepancies exist among aligners and variant callers. We developed a computational pipeline, SeqMule, to perform automated variant calling from NGS data on human genomes and exomes. SeqMule integrates computational-cluster-free parallelization capability built on top of the variant callers, and facilitates normalization/intersection of variant calls to generate consensus set with high confidence. SeqMule integrates 5 alignment tools, 5 variant calling algorithms and accepts various combinations all by one-line command, therefore allowing highly flexible yet fully automated variant calling. In a modern machine (2 Intel Xeon X5650 CPUs, 48 GB memory), when fast turn-around is needed, SeqMule generates annotated VCF files in a day from a 30X whole-genome sequencing data set; when more accurate calling is needed, SeqMule generates consensus call set that improves over single callers, as measured by both Mendelian error rate and consistency. SeqMule supports Sun Grid Engine for parallel processing, offers turn-key solution for deployment on Amazon Web Services, allows quality check, Mendelian error check, consistency evaluation, HTML-based reports. SeqMule is available at http://seqmule.openbioinformatics.org. Nature Publishing Group 2015-09-18 /pmc/articles/PMC4585643/ /pubmed/26381817 http://dx.doi.org/10.1038/srep14283 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Guo, Yunfei Ding, Xiaolei Shen, Yufeng Lyon, Gholson J. Wang, Kai SeqMule: automated pipeline for analysis of human exome/genome sequencing data |
title | SeqMule: automated pipeline for analysis of human exome/genome sequencing data |
title_full | SeqMule: automated pipeline for analysis of human exome/genome sequencing data |
title_fullStr | SeqMule: automated pipeline for analysis of human exome/genome sequencing data |
title_full_unstemmed | SeqMule: automated pipeline for analysis of human exome/genome sequencing data |
title_short | SeqMule: automated pipeline for analysis of human exome/genome sequencing data |
title_sort | seqmule: automated pipeline for analysis of human exome/genome sequencing data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585643/ https://www.ncbi.nlm.nih.gov/pubmed/26381817 http://dx.doi.org/10.1038/srep14283 |
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