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1.
Genome Res ; 29(9): 1555-1565, 2019 09.
Article in English | MEDLINE | ID: mdl-31439692

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 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.


Subject(s)
Computational Biology/methods , Germ-Line Mutation , Neoplasms/genetics , Child , Cloud Computing , Databases, Genetic , Genetic Predisposition to Disease , High-Throughput Nucleotide Sequencing , Humans , User-Computer Interface
2.
Stud Health Technol Inform ; 183: 251-6, 2013.
Article in English | MEDLINE | ID: mdl-23388293

ABSTRACT

The Pediatric Oncology Network Database, (www.pond4kids.org, POND), is a secure, web-based, multilingual pediatric hematology/oncology database created for use in countries with limited resources to meet various clinical data management needs including cancer registration, delivery of protocol-based care, outcome evaluation, and assessment of psychosocial support programs. Established as a part of the International Outreach Program at St. Jude Children's Research Hospital in Memphis, Tennessee, POND serves as a tool for oncology units to store patient data for easy retrieval and analysis and to achieve uniform data collection to facilitate meaningful comparison of information among centers. Launched in 2003, POND now has 233 sites registered with over 1,000 users in 66 countries. However, adoption and usage of POND varies widely among sites. This paper reviews some of the challenges to developing a global collaborative clinical platform based on the experiences of developing POND. The paper also presents a case study of POND use in Guatemala, where the Guatemalan National Oncology Unit (UNOP) has developed extensive internal and external global collaborations using POND.


Subject(s)
Databases, Factual , Hematology/methods , Information Dissemination/methods , Medical Oncology/methods , Outcome Assessment, Health Care/methods , Pediatrics/methods , Software , Cooperative Behavior , Internationality , Internet
3.
Stud Health Technol Inform ; 164: 227-31, 2011.
Article in English | MEDLINE | ID: mdl-21335715

ABSTRACT

The Pediatric Oncology Network Database, POND4Kids (www.pond4kids.org, POND), is an online, multilingual clinical database created for use by pediatric oncology units in countries with limited resources to meet various clinical data management needs including cancer registration, data collection and changes in treatment outcome. Established as a part of the International Outreach Program at St. Jude Children's Research Hospital in Memphis, Tennessee, POND aims to provide oncology units a tool to store patient data for easy retrieval and analysis and to achieve uniform data collection to facilitate meaningful comparison of information among centers. Currently, POND is being used to store clinical data on thousands of patients and measure their treatment improvement over a period of time. In 2009 POND included more than 100 pediatric oncology units; each has its own virtual private area. A case study of the UNOP Guatemala Clinic's use of POND is presented. On-going challenges at partner sites include inconsistent data collection methods, missing records, training for data managers, and slow or unreliable internet connections.


Subject(s)
Hospitals, Pediatric , Internet , Neoplasms , Registries , Cooperative Behavior , Humans , Internationality
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