NGS-Logistics: federated analysis of NGS sequence variants across multiple locations

NGS-Logistics: federated analysis of NGS sequence variants across multiple locations

As many personal genomes are being sequenced, collaborative analysis of those genomes has become essential. However, analysis of personal genomic data raises important privacy and confidentiality issues. We propose a methodology for federated analysis of sequence variants from personal genomes. Spec...

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Main Authors: Ardeshirdavani, Amin, Souche, Erika, Dehaspe, Luc, Van Houdt, Jeroen, Vermeesch, Joris Robert, Moreau, Yves
Format: Online
Language:English
Published: BioMed Central 2014
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4198698/
id pubmed-4198698
recordtype oai_dc
spelling pubmed-41986982014-10-18 NGS-Logistics: federated analysis of NGS sequence variants across multiple locations Ardeshirdavani, Amin Souche, Erika Dehaspe, Luc Van Houdt, Jeroen Vermeesch, Joris Robert Moreau, Yves Software As many personal genomes are being sequenced, collaborative analysis of those genomes has become essential. However, analysis of personal genomic data raises important privacy and confidentiality issues. We propose a methodology for federated analysis of sequence variants from personal genomes. Specific base-pair positions and/or regions are queried for samples to which the user has access but also for the whole population. The statistics results do not breach data confidentiality but allow further exploration of the data; researchers can negotiate access to relevant samples through pseudonymous identifiers. This approach minimizes the impact on data confidentiality while enabling powerful data analysis by gaining access to important rare samples. Our methodology is implemented in an open source tool called NGS-Logistics, freely available at https://ngsl.esat.kuleuven.be. BioMed Central 2014-09-17 /pmc/articles/PMC4198698/ /pubmed/25328540 http://dx.doi.org/10.1186/s13073-014-0071-9 Text en © Ardeshirdavani et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Ardeshirdavani, Amin
Souche, Erika
Dehaspe, Luc
Van Houdt, Jeroen
Vermeesch, Joris Robert
Moreau, Yves
spellingShingle Ardeshirdavani, Amin
Souche, Erika
Dehaspe, Luc
Van Houdt, Jeroen
Vermeesch, Joris Robert
Moreau, Yves
NGS-Logistics: federated analysis of NGS sequence variants across multiple locations
author_facet Ardeshirdavani, Amin
Souche, Erika
Dehaspe, Luc
Van Houdt, Jeroen
Vermeesch, Joris Robert
Moreau, Yves
author_sort Ardeshirdavani, Amin
title NGS-Logistics: federated analysis of NGS sequence variants across multiple locations
title_short NGS-Logistics: federated analysis of NGS sequence variants across multiple locations
title_full NGS-Logistics: federated analysis of NGS sequence variants across multiple locations
title_fullStr NGS-Logistics: federated analysis of NGS sequence variants across multiple locations
title_full_unstemmed NGS-Logistics: federated analysis of NGS sequence variants across multiple locations
title_sort ngs-logistics: federated analysis of ngs sequence variants across multiple locations
description As many personal genomes are being sequenced, collaborative analysis of those genomes has become essential. However, analysis of personal genomic data raises important privacy and confidentiality issues. We propose a methodology for federated analysis of sequence variants from personal genomes. Specific base-pair positions and/or regions are queried for samples to which the user has access but also for the whole population. The statistics results do not breach data confidentiality but allow further exploration of the data; researchers can negotiate access to relevant samples through pseudonymous identifiers. This approach minimizes the impact on data confidentiality while enabling powerful data analysis by gaining access to important rare samples. Our methodology is implemented in an open source tool called NGS-Logistics, freely available at https://ngsl.esat.kuleuven.be.
publisher BioMed Central
publishDate 2014
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4198698/
_version_ 1613145245371858944

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