PGen: large-scale genomic variations analysis workflow and browser in SoyKB. Liu, Y., Khan, S. M., Wang, J., Rynge, M., Zhang, Y., Zeng, S., Chen, S., Maldonado dos Santos, J. V., Valliyodan, B., Calyam, P. P., Merchant, N., Nguyen, H. T., Xu, D., & Joshi, T. BMC Bioinformatics, 17(13):337, 2016. ![PGen: large-scale genomic variations analysis workflow and browser in SoyKB [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex With the advances in next-generation sequencing (NGS) technology and significant reductions in sequencing costs, it is now possible to sequence large collections of germplasm in crops for detecting genome-scale genetic variations and to apply the knowledge towards improvements in traits. To efficiently facilitate large-scale NGS resequencing data analysis of genomic variations, we have developed PGen, an integrated and optimized workflow using the Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing (HPC) virtual system, iPlant cloud data storage resources and Pegasus workflow management system (Pegasus-WMS). The workflow allows users to identify single nucleotide polymorphisms (SNPs) and insertion-deletions (indels), perform SNP annotations and conduct copy number variation analyses on multiple resequencing datasets in a user-friendly and seamless way.
@Article{ liu2016,
Author = {Liu, Yang and Khan, Saad M. and Wang, Juexin and Rynge,
Mats and Zhang, Yuanxun and Zeng, Shuai and Chen, Shiyuan
and Maldonado dos Santos, Joao V. and Valliyodan, Babu and
Calyam, Prasad P. and Merchant, Nirav and Nguyen, Henry T.
and Xu, Dong and Joshi, Trupti},
Title = {PGen: large-scale genomic variations analysis workflow and
browser in SoyKB},
Journal = {BMC Bioinformatics},
Year = {2016},
Volume = {17},
Number = {13},
Pages = {337},
Abstract = {With the advances in next-generation sequencing (NGS)
technology and significant reductions in sequencing costs,
it is now possible to sequence large collections of
germplasm in crops for detecting genome-scale genetic
variations and to apply the knowledge towards improvements
in traits. To efficiently facilitate large-scale NGS
resequencing data analysis of genomic variations, we have
developed PGen, an integrated and optimized workflow using
the Extreme Science and Engineering Discovery Environment
(XSEDE) high-performance computing (HPC) virtual system,
iPlant cloud data storage resources and Pegasus workflow
management system (Pegasus-WMS). The workflow allows users
to identify single nucleotide polymorphisms (SNPs) and
insertion-deletions (indels), perform SNP annotations and
conduct copy number variation analyses on multiple
resequencing datasets in a user-friendly and seamless
way.},
ISSN = {1471-2105},
DOI = {10.1186/s12859-016-1227-y},
URL = {http://dx.doi.org/10.1186/s12859-016-1227-y}
}
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T.","Xu, D.","Joshi, T."],"bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Liu"],"firstnames":["Yang"],"suffixes":[]},{"propositions":[],"lastnames":["Khan"],"firstnames":["Saad","M."],"suffixes":[]},{"propositions":[],"lastnames":["Wang"],"firstnames":["Juexin"],"suffixes":[]},{"propositions":[],"lastnames":["Rynge"],"firstnames":["Mats"],"suffixes":[]},{"propositions":[],"lastnames":["Zhang"],"firstnames":["Yuanxun"],"suffixes":[]},{"propositions":[],"lastnames":["Zeng"],"firstnames":["Shuai"],"suffixes":[]},{"propositions":[],"lastnames":["Chen"],"firstnames":["Shiyuan"],"suffixes":[]},{"propositions":["Maldonado","dos"],"lastnames":["Santos"],"firstnames":["Joao","V."],"suffixes":[]},{"propositions":[],"lastnames":["Valliyodan"],"firstnames":["Babu"],"suffixes":[]},{"propositions":[],"lastnames":["Calyam"],"firstnames":["Prasad","P."],"suffixes":[]},{"propositions":[],"lastnames":["Merchant"],"firstnames":["Nirav"],"suffixes":[]},{"propositions":[],"lastnames":["Nguyen"],"firstnames":["Henry","T."],"suffixes":[]},{"propositions":[],"lastnames":["Xu"],"firstnames":["Dong"],"suffixes":[]},{"propositions":[],"lastnames":["Joshi"],"firstnames":["Trupti"],"suffixes":[]}],"title":"PGen: large-scale genomic variations analysis workflow and browser in SoyKB","journal":"BMC Bioinformatics","year":"2016","volume":"17","number":"13","pages":"337","abstract":"With the advances in next-generation sequencing (NGS) technology and significant reductions in sequencing costs, it is now possible to sequence large collections of germplasm in crops for detecting genome-scale genetic variations and to apply the knowledge towards improvements in traits. To efficiently facilitate large-scale NGS resequencing data analysis of genomic variations, we have developed PGen, an integrated and optimized workflow using the Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing (HPC) virtual system, iPlant cloud data storage resources and Pegasus workflow management system (Pegasus-WMS). The workflow allows users to identify single nucleotide polymorphisms (SNPs) and insertion-deletions (indels), perform SNP annotations and conduct copy number variation analyses on multiple resequencing datasets in a user-friendly and seamless way.","issn":"1471-2105","doi":"10.1186/s12859-016-1227-y","url":"http://dx.doi.org/10.1186/s12859-016-1227-y","bibtex":"@Article{\t liu2016,\n Author\t= {Liu, Yang and Khan, Saad M. and Wang, Juexin and Rynge,\n\t\t Mats and Zhang, Yuanxun and Zeng, Shuai and Chen, Shiyuan\n\t\t and Maldonado dos Santos, Joao V. and Valliyodan, Babu and\n\t\t Calyam, Prasad P. and Merchant, Nirav and Nguyen, Henry T.\n\t\t and Xu, Dong and Joshi, Trupti},\n Title\t\t= {PGen: large-scale genomic variations analysis workflow and\n\t\t browser in SoyKB},\n Journal\t= {BMC Bioinformatics},\n Year\t\t= {2016},\n Volume\t= {17},\n Number\t= {13},\n Pages\t\t= {337},\n Abstract\t= {With the advances in next-generation sequencing (NGS)\n\t\t technology and significant reductions in sequencing costs,\n\t\t it is now possible to sequence large collections of\n\t\t germplasm in crops for detecting genome-scale genetic\n\t\t variations and to apply the knowledge towards improvements\n\t\t in traits. 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