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Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline.

BMC bioinformatics | Jan 29, 2014

BACKGROUND: Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. RESULTS: To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. CONCLUSIONS: By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples.

Pubmed ID: 24475911 RIS Download

Mesh terms: Genome | Genomics | High-Throughput Nucleotide Sequencing | Humans | Internet | Software

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This is a list of tools and resources that we have found mentioned in this publication.


Human Gene Mutation Database

Curated database of known (published) gene lesions responsible for human inherited disease.

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COSMIC - Catalogue Of Somatic Mutations In Cancer

Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.

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GitHub

A web-based hosting service for software development projects that use the Git revision control system offering powerful collaboration, code review, and code management. It offers both paid plans for private repositories, and free accounts for open source projects. Large or small, every repository comes with the same powerful tools. These tools are open to the community for public projects and secure for private projects. Features include: * Integrated issue tracking * Collaborative code review * Easily manage teams within organizations * Text entry with understated power * A growing list of programming languages and data formats * On the desktop and in your pocket - Android app and mobile web views let you keep track of your projects on the go.

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OMIM

A comprehensive and detailed collection of human genes and genetic phenotypes, focusing on the relationship between phenotype and genotype. The full-text, referenced overviews in OMIM contain information on all known mendelian disorders and a variety of related genes. It is updated daily, and the entries contain copious links to other genetics resources.

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NCBI

A portal to biomedical and genomic information. NCBI creates public databases, conducts research in computational biology, develops software tools for analyzing genome data, and disseminates biomedical information for the better understanding of molecular processes affecting human health and disease.

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Picard

Java toolset for working with next generation sequencing data in the BAM format.

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GWAS: Catalog of Published Genome-Wide Association Studies

Database of genome-wide association study (GWAS) publications including only those attempting to assay at least 100,000 single nucleotide polymorphisms (SNPs). Publications are organized from most to least recent date of publication. Studies focusing only on candidate genes are excluded from this catalog. Studies are identified through weekly PubMed literature searches, daily NIH-distributed compilations of news and media reports, and occasional comparisons with an existing database of GWAS literature (HuGE Navigator).

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