Dataset Information

Epicontacts: Handling, visualisation and analysis of epidemiological contacts.

ABSTRACT: Epidemiological outbreak data is often captured in line list and contact format to facilitate contact tracing for outbreak control. epicontacts is an R package that provides a unique data structure for combining these data into a single object in order to facilitate more efficient visualisation and analysis. The package incorporates interactive visualisation functionality as well as network analysis techniques. Originally developed as part of the Hackout3 event, it is now developed, maintained and featured as part of the R Epidemics Consortium (RECON). The package is available for download from the Comprehensive R Archive Network (CRAN) and GitHub.

SUBMITTER: Nagraj VP

PROVIDER: S-EPMC6572866 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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epicontacts: Handling, visualisation and analysis of epidemiological contacts.

Nagraj V P VP Randhawa Nistara N Campbell Finlay F Crellen Thomas T Sudre Bertrand B Jombart Thibaut T

F1000Research 20180510

Epidemiological outbreak data is often captured in line list and contact format to facilitate contact tracing for outbreak control. <i>epicontacts</i> is an R package that provides a unique data structure for combining these data into a single object in order to facilitate more efficient visualisation and analysis. The package incorporates interactive visualisation functionality as well as network analysis techniques. Originally developed as part of the Hackout3 event, it is now developed, maint ...[more]

PMID: 31240097

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Project description:BackgroundNext Generation Sequencing (NGS) is a commonly used technology for studying the genetic basis of biological processes and it underpins the aspirations of precision medicine. However, there are significant challenges when dealing with NGS data. Firstly, a huge number of bioinformatics tools for a wide range of uses exist, therefore it is challenging to design an analysis pipeline. Secondly, NGS analysis is computationally intensive, requiring expensive infrastructure, and many medical and research centres do not have adequate high performance computing facilities and cloud computing is not always an option due to privacy and ownership issues. Finally, the interpretation of the results is not trivial and most available pipelines lack the utilities to favour this crucial step.ResultsWe have therefore developed a fast and efficient bioinformatics pipeline that allows for the analysis of DNA sequencing data, while requiring little computational effort and memory usage. DNAscan can analyse a whole exome sequencing sample in 1 h and a 40x whole genome sequencing sample in 13 h, on a midrange computer. The pipeline can look for single nucleotide variants, small indels, structural variants, repeat expansions and viral genetic material (or any other organism). Its results are annotated using a customisable variety of databases and are available for an on-the-fly visualisation with a local deployment of the gene.iobio platform. DNAscan is implemented in Python. Its code and documentation are available on GitHub: https://github.com/KHP-Informatics/DNAscan . Instructions for an easy and fast deployment with Docker and Singularity are also provided on GitHub.ConclusionsDNAscan is an extremely fast and computationally efficient pipeline for analysis, visualization and interpretation of NGS data. It is designed to provide a powerful and easy-to-use tool for applications in biomedical research and diagnostic medicine, at minimal computational cost. Its comprehensive approach will maximise the potential audience of users, bringing such analyses within the reach of non-specialist laboratories, and those from centres with limited funding available.

Dataset Information

Epicontacts: Handling, visualisation and analysis of epidemiological contacts.

Publications

epicontacts: Handling, visualisation and analysis of epidemiological contacts.

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