Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): a cloud-based platform for curating and classifying germline variants

Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the diatric cer Variant athogenicity nformation xchange (PeCanPIE), a web- and clo...

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Published in:	Genome research Vol. 29; no. 9; p. 1555
Main Authors:	Edmonson, Michael N, Patel, Aman N, Hedges, Dale J, Wang, Zhaoming, Rampersaud, Evadnie, Kesserwan, Chimene A, Zhou, Xin, Liu, Yanling, Newman, Scott, Rusch, Michael C, McLeod, Clay L, Wilkinson, Mark R, Rice, Stephen V, Soussi, Thierry, Taylor, J Paul, Benatar, Michael, Becksfort, Jared B, Nichols, Kim E, Robison, Leslie L, Downing, James R, Zhang, Jinghui
Format:	Journal Article
Language:	English
Published:	United States 01.09.2019
Subjects:	Child Cloud Computing Computational Biology - methods Databases, Genetic Genetic Predisposition to Disease Germ-Line Mutation High-Throughput Nucleotide Sequencing Humans Neoplasms - genetics User-Computer Interface
ISSN:	1549-5469, 1549-5469
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Abstract	Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the diatric cer Variant athogenicity nformation xchange (PeCanPIE), a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in variant call format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4000 pediatric cancer patients and serves as a repository for the expert-reviewed results. PeCanPIE was originally developed for pediatric cancer but can be easily extended for use for nonpediatric cancers and noncancer genetic diseases. Although PeCanPIE's web-based interface was designed to be accessible to non-bioinformaticians, its back-end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.
AbstractList	Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the diatric cer Variant athogenicity nformation xchange (PeCanPIE), a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in variant call format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4000 pediatric cancer patients and serves as a repository for the expert-reviewed results. PeCanPIE was originally developed for pediatric cancer but can be easily extended for use for nonpediatric cancers and noncancer genetic diseases. Although PeCanPIE's web-based interface was designed to be accessible to non-bioinformaticians, its back-end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use. Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE), a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in variant call format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4000 pediatric cancer patients and serves as a repository for the expert-reviewed results. PeCanPIE was originally developed for pediatric cancer but can be easily extended for use for nonpediatric cancers and noncancer genetic diseases. Although PeCanPIE's web-based interface was designed to be accessible to non-bioinformaticians, its back-end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE), a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in variant call format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4000 pediatric cancer patients and serves as a repository for the expert-reviewed results. PeCanPIE was originally developed for pediatric cancer but can be easily extended for use for nonpediatric cancers and noncancer genetic diseases. Although PeCanPIE's web-based interface was designed to be accessible to non-bioinformaticians, its back-end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.
Author	Nichols, Kim E Edmonson, Michael N Hedges, Dale J Newman, Scott Wilkinson, Mark R Kesserwan, Chimene A Downing, James R Liu, Yanling Patel, Aman N Zhou, Xin Rampersaud, Evadnie Rusch, Michael C Taylor, J Paul Zhang, Jinghui Benatar, Michael Soussi, Thierry Becksfort, Jared B Wang, Zhaoming Rice, Stephen V McLeod, Clay L Robison, Leslie L
Author_xml	– sequence: 1 givenname: Michael N orcidid: 0000-0003-0339-700X surname: Edmonson fullname: Edmonson, Michael N organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 2 givenname: Aman N orcidid: 0000-0002-5757-2697 surname: Patel fullname: Patel, Aman N organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 3 givenname: Dale J surname: Hedges fullname: Hedges, Dale J organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 4 givenname: Zhaoming surname: Wang fullname: Wang, Zhaoming organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 5 givenname: Evadnie surname: Rampersaud fullname: Rampersaud, Evadnie organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 6 givenname: Chimene A surname: Kesserwan fullname: Kesserwan, Chimene A organization: Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 7 givenname: Xin surname: Zhou fullname: Zhou, Xin organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 8 givenname: Yanling surname: Liu fullname: Liu, Yanling organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 9 givenname: Scott surname: Newman fullname: Newman, Scott organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 10 givenname: Michael C surname: Rusch fullname: Rusch, Michael C organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 11 givenname: Clay L surname: McLeod fullname: McLeod, Clay L organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 12 givenname: Mark R surname: Wilkinson fullname: Wilkinson, Mark R organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 13 givenname: Stephen V surname: Rice fullname: Rice, Stephen V organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 14 givenname: Thierry surname: Soussi fullname: Soussi, Thierry organization: INSERM, U1138, Équipe 11, Centre de Recherche des Cordeliers, 75006 Paris, France – sequence: 15 givenname: J Paul surname: Taylor fullname: Taylor, J Paul organization: Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 16 givenname: Michael surname: Benatar fullname: Benatar, Michael organization: Department of Neurology, University of Miami, Miami, Florida 33136, USA – sequence: 17 givenname: Jared B surname: Becksfort fullname: Becksfort, Jared B organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 18 givenname: Kim E surname: Nichols fullname: Nichols, Kim E organization: Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 19 givenname: Leslie L surname: Robison fullname: Robison, Leslie L organization: Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 20 givenname: James R surname: Downing fullname: Downing, James R organization: Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA – sequence: 21 givenname: Jinghui surname: Zhang fullname: Zhang, Jinghui organization: Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
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SubjectTerms	Child Cloud Computing Computational Biology - methods Databases, Genetic Genetic Predisposition to Disease Germ-Line Mutation High-Throughput Nucleotide Sequencing Humans Neoplasms - genetics User-Computer Interface
Title	Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): a cloud-based platform for curating and classifying germline variants
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